US6072893A
Expired / Lapsed
US
⏱️ 0.0 years remaining
Method and system for locating objects in an image
Assignee: Monument Peak Ventures LLC
•
Filing: 1999-01-06
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Granted: 2000-06-06
•
Expires: 2019-01-06
Abstract
Abstract A computer program product for locating first and second objects each having substantially the same physical characteristics, and the ratio of the distance between the first and second objects and the size of each object is substantially invariant, the computer program product comprises: a computer readable storage medium having a computer program stored thereon for performing the steps of: displaying a digital image on a graphical user interface; inputting to the interface an approximate position of each object for forming initial input positions; determining an estimate size of each object based on the distance obtained from the initial input positions of the first and second objects; forming a first searching window for the first object; the center of the first window is determined by the input position of the first object and the size of the first window is determined by the estimate size of the first object; reiteratively positioning a template on the first search window for determining a location that gives a best match of the first object relative to the template; forming a second searching window for the second object; the center of the second window is determined by the input position of the second object and the size of the second window is determined by the estimate size of the second object; and reiteratively positioning a template on the second search window for determining a location that gives a best match of the second object relative to the template.
Inventors
- 👤 Jiebo Luo
- 👤 Robert T. Gray
Bibliographic Details
Application Number
—
Jurisdiction
US
Data Source
google_patents
Last Synchronized
2026-10-29 17:26
CPC Classifications
G; G06; G06V; G06V40/00; G06V40/10; G06V40/18; G06V40/19; G06T; G06T7/00; G06T7/70; G06T7/73; G06T7/74; G06T2207/00; G06T2207/30; G06T2207/30216
Claims Analysis
Total Claims: 228
Claim 1
Independent Claim
233 words
A method for locating first and second objects each having substantially the same physical characteristics, and the ratio of the distance between the first and second objects and the size of each object is substantially invariant, the method comprising the steps of: (a) displaying a digital image on a graphical user interface; (b) inputting to the interface an approximate position of each object for forming initial input positions; (c) determining an estimate size of each object based on the distance obtained from the initial input positions of the first and second objects; (d) forming a first searching window for the first object; the center of the first window is determined by the input position of the first object and the size of the first window is determined by the estimate size of the first object; (e) reiteratively positioning a template on the first search window for determining a location that gives a desired match of the first object relative to the template; (f) forming a second searching window for the second object; the center of the second window is determined by the input position of the second object and the size of the second window is determined by the estimate size of the second object; and (g) reiteratively positioning a template on the second search window for determining a location that gives a desired match of the second object relative to the template.
Claim 2
Independent Claim
233 words
A method for locating first and second objects each having substantially the same physical characteristics, and the ratio of the distance between the first and second objects and the size of each object is substantially invariant, the method comprising the steps of: (a) displaying a digital image on a graphical user interface; (b) inputting to the interface an approximate position of each object for forming initial input positions; (c) determining an estimate size of each object based on the distance obtained from the initial input positions of the first and second objects; (d) forming a first searching window for the first object; the center of the first window is determined by the input position of the first object and the size of the first window is determined by the estimate size of the first object; (e) reiteratively positioning a template on the first search window for determining a location that gives a desired match of the first object relative to the template; (f) forming a second searching window for the second object; the center of the second window is determined by the input position of the second object and the size of the second window is determined by the estimate size of the second object; and (g) reiteratively positioning a template on the second search window for determining a location that gives a desired match of the second object relative to the template.
Claim 3
Dependent Claim
30 words
The method as in claim 1, further comprising the step of (h) determining a plurality of locations in each search window that give a desired matching response to the template.
Claim 4
Dependent Claim
31 words
The method as in claim 2 further comprising the step of finding the best pair of locations from all possible combinations of identified locations of both the first and second objects.
Claim 5
Dependent Claim
37 words
The method as in claim 3, wherein the step of finding best pair of locations includes computing a plurality of figures of merit and determining a pair of locations that give a best combined figure of merit.
Claim 6
Dependent Claim
33 words
The method as in claim 4, wherein computing a plurality of figures of merit includes computing individually or in combination an orientation, proximity, combined correlation score, proportion, profile, symmetry or evidence of mouth.
Claim 7
Dependent Claim
49 words
The method as in claim 5, wherein the first and second objects are first and second human eyes and wherein computing an orientation includes measuring the difference between the orientation of the line connecting the first and second eyes, and the average orientation of the first and second eyes.
Claim 8
Dependent Claim
25 words
The method as in claim 5, wherein computing a proximity includes measuring proximity of the first and second objects to the initial input positions, respectively.
Claim 9
Dependent Claim
27 words
The method as in claim 5, wherein computing a combined correlation score includes summing up the individual correlation scores obtained from the matching obtained in step (e1).
Claim 10
Dependent Claim
39 words
The method as in claim 5, wherein the first and second objects are first and second human eyes and wherein computing a proportion includes computing a distance between the first and second eyes for satisfying an anthropological prior model.
Claim 11
Dependent Claim
51 words
The method as in claim 5, wherein the first and second objects are first and second human eyes and wherein computing the profile includes pre-determining a model of the eye-to-eye profile and determining an actual profile from the image and computing a goodness-of-fit between the actual profile and the model profile.
Claim 12
Dependent Claim
41 words
The method as in claim 5, wherein the first and second objects are first and second human eyes and wherein computing the symmetry includes computing a symmetry between first and second halves of a face window determined by the eye locations.
Claim 13
Dependent Claim
41 words
The method as in claim 5, wherein the first and second objects are first and second human eyes and wherein computing the evidence of mouth includes computing strength and orientation of edges within a mouth window determined by the eye locations.
Claim 14
Dependent Claim
19 words
The method as in claim 2 further comprising the step of normalizing the template for maximizing robustness of matching.
Claim 15
Dependent Claim
24 words
The method as in claim 2 further comprising the step of creating a image block of the same size and orientation as the template.
Claim 16
Dependent Claim
20 words
The method as in claim 14 further comprising the step of normalizing the image block for maximizing robustness of matching.
Claim 17
Dependent Claim
29 words
The method as in claim 14 further comprising the step of extracting individual sub-zones in both the template and the image block, and performing cross-correlation for each corresponding sub-zone.
Claim 18
Dependent Claim
30 words
The method as in claim 14 further comprising the step of computing the overall cross-correlation score for the image block if the cross-correlation score for each sub-zone exceeds a threshold.
Claim 19
Dependent Claim
20 words
The method as in claim 2 further comprising the step of identifying the locations that give locally maximum cross-correlation score.
Claim 20
Independent Claim
234 words
A method for locating first and second objects each having substantially the same physical characteristics, and the ratio of the distance between the first and second objects and the size of each object is substantially invariant, the method comprising the steps of: (a) displaying a digital image on a graphical user interface; (b) inputting to the interface an approximate position of each object for forming initial input positions; (c) determining an estimate orientation of each object based on an angle derived from the initial input positions of the first and second objects; (d) forming a first searching window for the first object; the center of the first window is determined by the initial input position of the first object and the size of the first window is determined by the estimate size of the first object; (e) reiteratively positioning a template on the first search window for determining a location that gives a desired match of the first object relative to the template; and (f) forming a second searching window for the first object; the center of the second window is determined by the input position of the first object and the size of the second window is determined by the estimate size of the first object; (g) reiteratively positioning a template on the second search window for determining a location that gives a desired match of the first object relative to the template.
Claim 21
Independent Claim
234 words
A method for locating first and second objects each having substantially the same physical characteristics, and the ratio of the distance between the first and second objects and the size of each object is substantially invariant, the method comprising the steps of: (a) displaying a digital image on a graphical user interface; (b) inputting to the interface an approximate position of each object for forming initial input positions; (c) determining an estimate orientation of each object based on an angle derived from the initial input positions of the first and second objects; (d) forming a first searching window for the first object; the center of the first window is determined by the initial input position of the first object and the size of the first window is determined by the estimate size of the first object; (e) reiteratively positioning a template on the first search window for determining a location that gives a desired match of the first object relative to the template; and (f) forming a second searching window for the first object; the center of the second window is determined by the input position of the first object and the size of the second window is determined by the estimate size of the first object; (g) reiteratively positioning a template on the second search window for determining a location that gives a desired match of the first object relative to the template.
Claim 22
Dependent Claim
22 words
The method as in claim 19 further comprising determining a plurality of locations that give a desired matching response to the template.
Claim 23
Dependent Claim
31 words
The method as in claim 19 further comprising the step of finding the best pair of locations from all possible combinations of identified locations of both the first and second objects.
Claim 24
Dependent Claim
37 words
The method as in claim 21, wherein the step of finding best pair of locations includes computing a plurality of figures of merit and determining a pair of locations that give a best combined figure of merit.
Claim 25
Dependent Claim
33 words
The method as in claim 22, wherein computing a plurality of figures of merit includes computing individually or in combination an orientation, proximity, combined correlation score, proportion, profile, symmetry or evidence of mouth.
Claim 26
Dependent Claim
49 words
The method as in claim 23, wherein the first and second objects are first and second human eyes and wherein computing an orientation includes measuring the difference between the orientation of the line connecting the first and second eyes, and the average orientation of the first and second eyes.
Claim 27
Dependent Claim
25 words
The method as in claim 23, wherein computing a proximity includes measuring proximity of the first and second objects to the initial input positions, respectively.
Claim 28
Dependent Claim
27 words
The method as in claim 23, wherein computing a combined correlation score includes summing up the individual correlation scores obtained from the matching obtained in step (e1).
Claim 29
Dependent Claim
39 words
The method as in claim 23, wherein the first and second objects are first and second human eyes and wherein computing a proportion includes computing a distance between the first and second eyes for satisfying an anthropological prior model.
Claim 30
Dependent Claim
51 words
The method as in claim 23, wherein the first and second objects are first and second human eyes and wherein computing the profile includes pre-determining a model of the eye-to-eye profile and determining an actual profile from the image and computing a goodness-of-fit between the actual profile and the model profile.
Claim 31
Dependent Claim
41 words
The method as in claim 23, wherein the first and second objects are first and second human eyes and wherein computing the symmetry includes computing a symmetry between first and second halves of a face window determined by the eye locations.
Claim 32
Dependent Claim
41 words
The method as in claim 23, wherein the first and second objects are first and second human eyes and wherein computing the evidence of mouth includes computing strength and orientation of edges within a mouth window determined by the eye locations.
Claim 33
Dependent Claim
19 words
The method as in claim 20 further comprising the step of normalizing the template for maximizing robustness of matching.
Claim 34
Dependent Claim
24 words
The method as in claim 20 further comprising the step of creating a image block of the same size and orientation as the template.
Claim 35
Dependent Claim
20 words
The method as in claim 32 further comprising the step of normalizing the image block for maximizing robustness of matching.
Claim 36
Dependent Claim
29 words
The method as in claim 32 further comprising the step of extracting individual sub-zones in both the template and the image block, and performing cross-correlation for each corresponding sub-zone.
Claim 37
Dependent Claim
30 words
The method as in claim 32 further comprising the step of computing the overall cross-correlation score for the image block if the cross-correlation score for each sub-zone exceeds a threshold.
Claim 38
Dependent Claim
20 words
The method as in claim 20 further comprising the step of identifying the locations that give locally maximum cross-correlation score.
Claim 39
Independent Claim
193 words
A method for locating first and second objects each having substantially the same physical characteristics, and the ratio of the distance between the first and second objects and the size of each object is substantially invariant, the method comprising the steps of: (a) displaying a digital image on a graphical user interface; (b) inputting to the interface an approximate position of each object for forming initial input positions; (c) determining an estimate orientation of each object based on an angle derived from the initial input positions of the first and second objects; (d) determining an estimate size of each object based on the distance obtained from the initial input positions of the first and second objects; (e) forming a searching window for the first object; the center of the window is determined by the input position of the first object and the size of the window is determined by the estimate size of the first object; (f) reiteratively positioning a template on the search window for determining a location that gives a desired match of the first object relative to the template; and (g) repeating steps (e) and (f) for the second object.
Claim 40
Independent Claim
193 words
A method for locating first and second objects each having substantially the same physical characteristics, and the ratio of the distance between the first and second objects and the size of each object is substantially invariant, the method comprising the steps of: (a) displaying a digital image on a graphical user interface; (b) inputting to the interface an approximate position of each object for forming initial input positions; (c) determining an estimate orientation of each object based on an angle derived from the initial input positions of the first and second objects; (d) determining an estimate size of each object based on the distance obtained from the initial input positions of the first and second objects; (e) forming a searching window for the first object; the center of the window is determined by the input position of the first object and the size of the window is determined by the estimate size of the first object; (f) reiteratively positioning a template on the search window for determining a location that gives a desired match of the first object relative to the template; and (g) repeating steps (e) and (f) for the second object.
Claim 41
Dependent Claim
30 words
The method as in claim 37, further comprising the step of (h) determining a plurality of locations in each search window that give a desired matching response to the template.
Claim 42
Dependent Claim
31 words
The method as in claim 38 further comprising the step of finding the best pair of locations from all possible combinations of identified locations of both the first and second objects.
Claim 43
Dependent Claim
37 words
The method as in claim 39, wherein the step of finding best pair of locations includes computing a plurality of figures of merit and determining a pair of locations that give a best combined figure of merit.
Claim 44
Dependent Claim
33 words
The method as in claim 40, wherein computing a plurality of figures of merit includes computing individually or in combination an orientation, proximity, combined correlation score, proportion, profile, symmetry or evidence of mouth.
Claim 45
Dependent Claim
49 words
The method as in claim 41, wherein the first and second objects are first and second human eyes and wherein computing an orientation includes measuring the difference between the orientation of the line connecting the first and second eyes, and the average orientation of the first and second eyes.
Claim 46
Dependent Claim
25 words
The method as in claim 41, wherein computing a proximity includes measuring proximity of the first and second objects to the initial input positions, respectively.
Claim 47
Dependent Claim
27 words
The method as in claim 41, wherein computing a combined correlation score includes summing up the individual correlation scores obtained from the matching obtained in step (e1).
Claim 48
Dependent Claim
39 words
The method as in claim 41, wherein the first and second objects are first and second human eyes and wherein computing a proportion includes computing a distance between the first and second eyes for satisfying an anthropological prior model.
Claim 49
Dependent Claim
51 words
The method as in claim 41, wherein the first and second objects are first and second human eyes and wherein computing the profile includes pre-determining a model of the eye-to-eye profile and determining an actual profile from the image and computing a goodness-of-fit between the actual profile and the model profile.
Claim 50
Dependent Claim
41 words
The method as in claim 41, wherein the first and second objects are first and second human eyes and wherein computing the symmetry includes computing a symmetry between first and second halves of a face window determined by the eye locations.
Claim 51
Dependent Claim
41 words
The method as in claim 41, wherein the first and second objects are first and second human eyes and wherein computing the evidence of mouth includes computing strength and orientation of edges within a mouth window determined by the eye locations.
Claim 52
Dependent Claim
19 words
The method as in claim 38 further comprising the step of normalizing the template for maximizing robustness of matching.
Claim 53
Dependent Claim
24 words
The method as in claim 38 further comprising the step of creating a image block of the same size and orientation as the template.
Claim 54
Dependent Claim
20 words
The method as in claim 50 further comprising the step of normalizing the image block for maximizing robustness of matching.
Claim 55
Dependent Claim
29 words
The method as in claim 50 further comprising the step of extracting individual sub-zones in both the template and the image block, and performing cross-correlation for each corresponding sub-zone.
Claim 56
Dependent Claim
30 words
The method as in claim 50 further comprising the step of computing the overall cross-correlation score for the image block if the cross-correlation score for each sub-zone exceeds a threshold.
Claim 57
Dependent Claim
20 words
The method as in claim 38 further comprising the step of identifying the locations that give locally maximum cross-correlation score.
Claim 58
Independent Claim
241 words
A method for locating first and second objects in an image each object having substantially the same physical characteristics, and the ratio of the distance between the first and second objects and the size of each object is substantially invariant, the method comprising the steps of: (a) displaying a digital image on a graphical user interface; (b) estimating an approximate position of each object for forming initial input positions based on a format of the image; (c) determining an estimate size of each object based on the distance obtained from the initial input positions of the first and second objects; (d) forming a first searching window for the first object; the center of the first window is determined by the input position of the first object and the size of the first window is determined by the estimate size of the first object; (e) reiteratively positioning a template on the first search window for determining a location that gives a desired match of the first object relative to the template; (f) forming a second searching window for the second object; the center of the second window is determined by the input position of the second object and the size of the second window is determined by the estimate size of the second object; and (g) reiteratively positioning a template on the second search window for determining a location that gives a desired match of the second object relative to the template.
Claim 59
Independent Claim
241 words
A method for locating first and second objects in an image each object having substantially the same physical characteristics, and the ratio of the distance between the first and second objects and the size of each object is substantially invariant, the method comprising the steps of: (a) displaying a digital image on a graphical user interface; (b) estimating an approximate position of each object for forming initial input positions based on a format of the image; (c) determining an estimate size of each object based on the distance obtained from the initial input positions of the first and second objects; (d) forming a first searching window for the first object; the center of the first window is determined by the input position of the first object and the size of the first window is determined by the estimate size of the first object; (e) reiteratively positioning a template on the first search window for determining a location that gives a desired match of the first object relative to the template; (f) forming a second searching window for the second object; the center of the second window is determined by the input position of the second object and the size of the second window is determined by the estimate size of the second object; and (g) reiteratively positioning a template on the second search window for determining a location that gives a desired match of the second object relative to the template.
Claim 60
Dependent Claim
30 words
The method as in claim 55, further comprising the step of (h) determining a plurality of locations in each search window that give a desired matching response to the template.
Claim 61
Dependent Claim
31 words
The method as in claim 56 further comprising the step of finding the best pair of locations from all possible combinations of identified locations of both the first and second objects.
Claim 62
Dependent Claim
37 words
The method as in claim 57, wherein the step of finding best pair of locations includes computing a plurality of figures of merit and determining a pair of locations that give a best combined figure of merit.
Claim 63
Dependent Claim
33 words
The method as in claim 58, wherein computing a plurality of figures of merit includes computing individually or in combination an orientation, proximity, combined correlation score, proportion, profile, symmetry or evidence of mouth.
Claim 64
Dependent Claim
49 words
The method as in claim 59, wherein the first and second objects are first and second human eyes and wherein computing an orientation includes measuring the difference between the orientation of the line connecting the first and second eyes, and the average orientation of the first and second eyes.
Claim 65
Dependent Claim
25 words
The method as in claim 59, wherein computing a proximity includes measuring proximity of the first and second objects to the initial input positions, respectively.
Claim 66
Dependent Claim
27 words
The method as in claim 59, wherein computing a combined correlation score includes summing up the individual correlation scores obtained from the matching obtained in step (e).
Claim 67
Dependent Claim
39 words
The method as in claim 59, wherein the first and second objects are first and second human eyes and wherein computing a proportion includes computing a distance between the first and second eyes for satisfying an anthropological prior model.
Claim 68
Dependent Claim
51 words
The method as in claim 59, wherein the first and second objects are first and second human eyes and wherein computing the profile includes pre-determining a model of the eye-to-eye profile and determining an actual profile from the image and computing a goodness-of-fit between the actual profile and the model profile.
Claim 69
Dependent Claim
41 words
The method as in claim 59, wherein the first and second objects are first and second human eyes and wherein computing the symmetry includes computing a symmetry between first and second halves of a face window determined by the eye locations.
Claim 70
Dependent Claim
41 words
The method as in claim 59, wherein the first and second objects are first and second human eyes and wherein computing the evidence of mouth includes computing strength and orientation of edges within a mouth window determined by the eye locations.
Claim 71
Dependent Claim
19 words
The method as in claim 56 further comprising the step of normalizing the template for maximizing robustness of matching.
Claim 72
Dependent Claim
24 words
The method as in claim 56 further comprising the step of creating a image block of the same size and orientation as the template.
Claim 73
Dependent Claim
20 words
The method as in claim 68 further comprising the step of normalizing the image block for maximizing robustness of matching.
Claim 74
Dependent Claim
29 words
The method as in claim 68 further comprising the step of extracting individual sub-zones in both the template and the image block, and performing cross-correlation for each corresponding sub-zone.
Claim 75
Dependent Claim
30 words
The method as in claim 68 further comprising the step of computing the overall cross-correlation score for the image block if the cross-correlation score for each sub-zone exceeds a threshold.
Claim 76
Dependent Claim
20 words
The method as in claim 56 further comprising the step of identifying the locations that give locally maximum cross-correlation score.
Claim 77
Independent Claim
231 words
A method for locating first and second objects each having substantially the same physical characteristics, and the ratio of the distance between the first and second objects and the size of each object is substantially invariant, the method comprising the steps of: (a) displaying a digital image on a graphical user interface; (b) estimating an approximate position of each object for forming initial input positions; (c) determining an estimate orientation of each object based on an angle derived from the initial input positions of the first and second objects; (d) forming a first searching window for the first object; the center of the first window is determined by the initial input position of the first object and the size of the first window is determined by the estimate size of the first object; (e) reiteratively positioning a template on the first search window for determining a location that gives a desired match of the first object relative to the template; and (f) forming a second searching window for the first object; the center of the second window is determined by the input position of the first object and the size of the second window is determined by the estimate size of the first object; (g) reiteratively positioning a template on the second search window for determining a location that gives a desired match of the first object relative to the template.
Claim 78
Independent Claim
231 words
A method for locating first and second objects each having substantially the same physical characteristics, and the ratio of the distance between the first and second objects and the size of each object is substantially invariant, the method comprising the steps of: (a) displaying a digital image on a graphical user interface; (b) estimating an approximate position of each object for forming initial input positions; (c) determining an estimate orientation of each object based on an angle derived from the initial input positions of the first and second objects; (d) forming a first searching window for the first object; the center of the first window is determined by the initial input position of the first object and the size of the first window is determined by the estimate size of the first object; (e) reiteratively positioning a template on the first search window for determining a location that gives a desired match of the first object relative to the template; and (f) forming a second searching window for the first object; the center of the second window is determined by the input position of the first object and the size of the second window is determined by the estimate size of the first object; (g) reiteratively positioning a template on the second search window for determining a location that gives a desired match of the first object relative to the template.
Claim 79
Dependent Claim
22 words
The method as in claim 73 further comprising determining a plurality of locations that give a desired matching response to the template.
Claim 80
Dependent Claim
31 words
The method as in claim 73 further comprising the step of finding the best pair of locations from all possible combinations of identified locations of both the first and second objects.
Claim 81
Dependent Claim
37 words
The method as in claim 75, wherein the step of finding best pair of locations includes computing a plurality of figures of merit and determining a pair of locations that give a best combined figure of merit.
Claim 82
Dependent Claim
33 words
The method as in claim 76, wherein computing a plurality of figures of merit includes computing individually or in combination an orientation, proximity, combined correlation score, proportion, profile, symmetry or evidence of mouth.
Claim 83
Dependent Claim
49 words
The method as in claim 77, wherein the first and second objects are first and second human eyes and wherein computing an orientation includes measuring the difference between the orientation of the line connecting the first and second eyes, and the average orientation of the first and second eyes.
Claim 84
Dependent Claim
25 words
The method as in claim 77, wherein computing a proximity includes measuring proximity of the first and second objects to the initial input positions, respectively.
Claim 85
Dependent Claim
27 words
The method as in claim 77, wherein computing a combined correlation score includes summing up the individual correlation scores obtained from the matching obtained in step (e1).
Claim 86
Dependent Claim
39 words
The method as in claim 77, wherein the first and second objects are first and second human eyes and wherein computing a proportion includes computing a distance between the first and second eyes for satisfying an anthropological prior model.
Claim 87
Dependent Claim
51 words
The method as in claim 77, wherein the first and second objects are first and second human eyes and wherein computing the profile includes pre-determining a model of the eye-to-eye profile and determining an actual profile from the image and computing a goodness-of-fit between the actual profile and the model profile.
Claim 88
Dependent Claim
41 words
The method as in claim 77, wherein the first and second objects are first and second human eyes and wherein computing the symmetry includes computing a symmetry between first and second halves of a face window determined by the eye locations.
Claim 89
Dependent Claim
41 words
The method as in claim 77, wherein the first and second objects are first and second human eyes and wherein computing the evidence of mouth includes computing strength and orientation of edges within a mouth window determined by the eye locations.
Claim 90
Dependent Claim
19 words
The method as in claim 74 further comprising the step of normalizing the template for maximizing robustness of matching.
Claim 91
Dependent Claim
24 words
The method as in claim 74 further comprising the step of creating a image block of the same size and orientation as the template.
Claim 92
Dependent Claim
20 words
The method as in claim 86 further comprising the step of normalizing the image block for maximizing robustness of matching.
Claim 93
Dependent Claim
29 words
The method as in claim 87 further comprising the step of extracting individual sub-zones in both the template and the image block, and performing cross-correlation for each corresponding sub-zone.
Claim 94
Dependent Claim
30 words
The method as in claim 87 further comprising the step of computing the overall cross-correlation score for the image block if the cross-correlation score for each sub-zone exceeds a threshold.
Claim 95
Dependent Claim
20 words
The method as in claim 75 further comprising the step of identifying the locations that give locally maximum cross-correlation score.
Claim 96
Independent Claim
201 words
A method for locating first and second objects in an image each object having substantially the same physical characteristics, and the ratio of the distance between the first and second objects and the size of each object is substantially invariant, the method comprising the steps of: (a) displaying a digital image on a graphical user interface; (b) estimating an approximate position of each object for forming initial input positions based on a format of the image; (c) determining an estimate orientation of each object based on an angle derived from the initial input positions of the first and second objects; (d) determining an estimate size of each object based on the distance obtained from the initial input positions of the first and second objects; (e) forming a searching window for the first object; the center of the window is determined by the input position of the first object and the size of the window is determined by the estimate size of the first object; (f) reiteratively positioning a template on the search window for determining a location that gives a desired match of the first object relative to the template; and (g) repeating steps (e) and (f) for the second object.
Claim 97
Independent Claim
201 words
A method for locating first and second objects in an image each object having substantially the same physical characteristics, and the ratio of the distance between the first and second objects and the size of each object is substantially invariant, the method comprising the steps of: (a) displaying a digital image on a graphical user interface; (b) estimating an approximate position of each object for forming initial input positions based on a format of the image; (c) determining an estimate orientation of each object based on an angle derived from the initial input positions of the first and second objects; (d) determining an estimate size of each object based on the distance obtained from the initial input positions of the first and second objects; (e) forming a searching window for the first object; the center of the window is determined by the input position of the first object and the size of the window is determined by the estimate size of the first object; (f) reiteratively positioning a template on the search window for determining a location that gives a desired match of the first object relative to the template; and (g) repeating steps (e) and (f) for the second object.
Claim 98
Dependent Claim
30 words
The method as in claim 91, further comprising the step of (h) determining a plurality of locations in each search window that give a desired matching response to the template.
Claim 99
Dependent Claim
31 words
The method as in claim 92 further comprising the step of finding the best pair of locations from all possible combinations of identified locations of both the first and second objects.
Claim 100
Dependent Claim
37 words
The method as in claim 93, wherein the step of finding best pair of locations includes computing a plurality of figures of merit and determining a pair of locations that give a best combined figure of merit.
Claim 101
Dependent Claim
33 words
The method as in claim 93, wherein computing a plurality of figures of merit includes computing individually or in combination an orientation, proximity, combined correlation score, proportion, profile, symmetry or evidence of mouth.
Claim 102
Dependent Claim
49 words
The method as in claim 95, wherein the first and second objects are first and second human eyes and wherein computing an orientation includes measuring the difference between the orientation of the line connecting the first and second eyes, and the average orientation of the first and second eyes.
Claim 103
Dependent Claim
25 words
The method as in claim 95, wherein computing a proximity includes measuring proximity of the first and second objects to the initial input positions, respectively.
Claim 104
Dependent Claim
27 words
The method as in claim 95, wherein computing a combined correlation score includes summing up the individual correlation scores obtained from the matching obtained in step (e1).
Claim 105
Dependent Claim
39 words
The method as in claim 95, wherein the first and second objects are first and second human eyes and wherein computing a proportion includes computing a distance between the first and second eyes for satisfying an anthropological prior model.
Claim 106
Dependent Claim
51 words
The method as in claim 95, wherein the first and second objects are first and second human eyes and wherein computing the profile includes pre-determining a model of the eye-to-eye profile and determining an actual profile from the image and computing a goodness-of-fit between the actual profile and the model profile.
Claim 107
Dependent Claim
41 words
The method as in claim 95, wherein the first and second objects are first and second human eyes and wherein computing the symmetry includes computing a symmetry between first and second halves of a face window determined by the eye locations.
Claim 108
Dependent Claim
41 words
The method as in claim 95, wherein the first and second objects are first and second human eyes and wherein computing the evidence of mouth includes computing strength and orientation of edges within a mouth window determined by the eye locations.
Claim 109
Dependent Claim
19 words
The method as in claim 92 further comprising the step of normalizing the template for maximizing robustness of matching.
Claim 110
Dependent Claim
24 words
The method as in claim 92 further comprising the step of creating a image block of the same size and orientation as the template.
Claim 111
Dependent Claim
20 words
The method as in claim 104 further comprising the step of normalizing the image block for maximizing robustness of matching.
Claim 112
Dependent Claim
29 words
The method as in claim 104 further comprising the step of extracting individual sub-zones in both the template and the image block, and performing cross-correlation for each corresponding sub-zone.
Claim 113
Dependent Claim
30 words
The method as in claim 104 further comprising the step of computing the overall cross-correlation score for the image block if the cross-correlation score for each sub-zone exceeds a threshold.
Claim 114
Dependent Claim
20 words
The method as in claim 92 further comprising the step of identifying the locations that give locally maximum cross-correlation score.
Claim 115
Independent Claim
244 words
A system for locating first and second objects each having substantially the same physical characteristics, and the ratio of the distance between the first and second objects and the size of each object is substantially invariant, the system comprising: (a) means for displaying a digital image on a graphical user interface; (b) means for inputting to the interface an approximate position of each object for forming initial input positions; (c) means for determining an estimate size of each object based on the distance obtained from the initial input positions of the first and second objects; (d) means for forming a first searching window for the first object; the center of the first window is determined by the input position of the first object and the size of the first window is determined by the estimate size of the first object; (e) means for reiteratively positioning a template on the first search window for determining a location that gives a desired match of the first object relative to the template; (f) means for forming a second searching window for the second object; the center of the second window is determined by the input position of the second object and the size of the second window is determined by the estimate size of the second object; and (g) means for reiteratively positioning a template on the second search window for determining a location that gives a desired match of the second object relative to the template.
Claim 116
Independent Claim
244 words
A system for locating first and second objects each having substantially the same physical characteristics, and the ratio of the distance between the first and second objects and the size of each object is substantially invariant, the system comprising: (a) means for displaying a digital image on a graphical user interface; (b) means for inputting to the interface an approximate position of each object for forming initial input positions; (c) means for determining an estimate size of each object based on the distance obtained from the initial input positions of the first and second objects; (d) means for forming a first searching window for the first object; the center of the first window is determined by the input position of the first object and the size of the first window is determined by the estimate size of the first object; (e) means for reiteratively positioning a template on the first search window for determining a location that gives a desired match of the first object relative to the template; (f) means for forming a second searching window for the second object; the center of the second window is determined by the input position of the second object and the size of the second window is determined by the estimate size of the second object; and (g) means for reiteratively positioning a template on the second search window for determining a location that gives a desired match of the second object relative to the template.
Claim 117
Dependent Claim
29 words
The system as in claim 108, further comprising (h) means for determining a plurality of locations in each search window that give a desired matching response to the template.
Claim 118
Dependent Claim
31 words
The system as in claim 110 further comprising means for finding the best pair of locations from all possible combinations of identified locations of both the first and second objects .
Claim 119
Dependent Claim
39 words
The system as in claim 111, wherein the means for finding best pair of locations includes means for computing a plurality of figures of merit and determining a pair of locations that give a best combined figure of merit.
Claim 120
Dependent Claim
38 words
The system as in claim 112, wherein the means for computing a plurality of figures of merit includes means for computing individually or in combination an orientation, proximity, combined correlation score, proportion, profile, symmetry or evidence of mouth.
Claim 121
Dependent Claim
49 words
The system as in claim 113, wherein the first and second objects are first and second human eyes and wherein computing an orientation includes measuring the difference between the orientation of the line connecting the first and second eyes, and the average orientation of the first and second eyes.
Claim 122
Dependent Claim
25 words
The system as in claim 113, wherein computing a proximity includes measuring proximity of the first and second objects to the initial input positions, respectively.
Claim 123
Dependent Claim
31 words
The system as in claim 113, wherein the means for computing a combined correlation score includes means for summing up the individual correlation scores obtained from the matching obtained in (e).
Claim 124
Dependent Claim
43 words
The system as in claim 113, wherein the first and second objects are first and second human eyes and wherein means for computing a proportion includes means for computing a distance between the first and second eyes for satisfying an anthropological prior model.
Claim 125
Dependent Claim
60 words
The system as in claim 113, wherein the first and second objects are first and second human eyes and wherein the means for computing the profile includes means for pre-determining a model of the eye-to-eye profile and means for determining an actual profile from the image and means for computing a goodness-of-fit between the actual profile and the model profile.
Claim 126
Dependent Claim
46 words
The system as in claim 113, wherein the first and second objects are first and second human eyes and wherein the means for computing the symmetry includes means for computing a symmetry between first and second halves of a face window determined by the eye locations.
Claim 127
Dependent Claim
46 words
The system as in claim 113, wherein the first and second objects are first and second human eyes and wherein the means for computing the evidence of mouth includes means for computing strength and orientation of edges within a mouth window determined by the eye locations.
Claim 128
Dependent Claim
18 words
The system as in claim 110 further comprising means for normalizing the template for maximizing robustness of matching.
Claim 129
Dependent Claim
23 words
The system as in claim 110 further comprising means for creating a image block of the same size and orientation as the template.
Claim 130
Dependent Claim
19 words
The system as in claim 122 further comprising means for normalizing the image block for maximizing robustness of matching.
Claim 131
Dependent Claim
30 words
The system as in claim 122 further comprising means for extracting individual sub-zones in both the template and the image block, and means for performing cross-correlation for each corresponding sub-zone.
Claim 132
Dependent Claim
28 words
The system as in claim 122 further comprising means for computing overall cross-correlation score for the image block if the cross-correlation score for each sub-zone exceeds a threshold.
Claim 133
Dependent Claim
19 words
The system as in claim 110 further comprising means for identifying the locations that give locally maximum cross-correlation score.
Claim 134
Independent Claim
245 words
A system for locating first and second objects each having substantially the same physical characteristics, and the ratio of the distance between the first and second objects and the size of each object is substantially invariant, the system comprising: (a) means for displaying a digital image on a graphical user interface; (b) means for inputting to the interface an approximate position of each object for forming initial input positions; (c) means for determining an estimate orientation of each object based on an angle derived from the initial input positions of the first and second objects; (d) means for forming a first searching window for the first object; the center of the first window is determined by the initial input position of the first object and the size of the first window is determined by the estimate size of the first object; (e) means for reiteratively positioning a template on the first search window for determining a location that gives a desired match of the first object relative to the template; and (f) means for forming a second searching window for the first object; the center of the second window is determined by the input position of the first object and the size of the second window is determined by the estimate size of the first object; (g) means for reiteratively positioning a template on the second search window for determining a location that gives a desired match of the first object relative to the template.
Claim 135
Independent Claim
245 words
A system for locating first and second objects each having substantially the same physical characteristics, and the ratio of the distance between the first and second objects and the size of each object is substantially invariant, the system comprising: (a) means for displaying a digital image on a graphical user interface; (b) means for inputting to the interface an approximate position of each object for forming initial input positions; (c) means for determining an estimate orientation of each object based on an angle derived from the initial input positions of the first and second objects; (d) means for forming a first searching window for the first object; the center of the first window is determined by the initial input position of the first object and the size of the first window is determined by the estimate size of the first object; (e) means for reiteratively positioning a template on the first search window for determining a location that gives a desired match of the first object relative to the template; and (f) means for forming a second searching window for the first object; the center of the second window is determined by the input position of the first object and the size of the second window is determined by the estimate size of the first object; (g) means for reiteratively positioning a template on the second search window for determining a location that gives a desired match of the first object relative to the template.
Claim 136
Dependent Claim
24 words
The system as in claim 127 further comprising means for determining a plurality of locations that give a desired matching response to the template.
Claim 137
Dependent Claim
30 words
The system as in claim 127 further comprising means for finding the best pair of locations from all possible combinations of identified locations of both the first and second objects.
Claim 138
Dependent Claim
41 words
The system as in claim 129, wherein the means for finding best pair of locations includes means for computing a plurality of figures of merit and means for determining a pair of locations that give a best combined figure of merit.
Claim 139
Dependent Claim
37 words
The system as in claim 130, wherein means for computing a plurality of figures of merit includes means for computing individually or in combination an orientation, proximity, combined correlation score, proportion, profile, symmetry or evidence of mouth.
Claim 140
Dependent Claim
56 words
The system as in claim 131, wherein the first and second objects are first and second human eyes and wherein the means for computing an orientation includes means for measuring the difference between the orientation of the line connecting the first and second eyes, and means for the average orientation of the first and second eyes.
Claim 141
Dependent Claim
30 words
The system as in claim 131, wherein the means for computing a proximity includes means for measuring proximity of the first and second objects to the initial input positions, respectively.
Claim 142
Dependent Claim
31 words
The system as in claim 131, wherein the means for computing a combined correlation score includes means for summing up the individual correlation scores obtained from the matching obtained in (e).
Claim 143
Dependent Claim
44 words
The system as in claim 131, wherein the first and second objects are first and second human eyes and wherein the means for computing a proportion includes means for computing a distance between the first and second eyes for satisfying an anthropological prior model.
Claim 144
Dependent Claim
58 words
The system as in claim 131, wherein the first and second objects are first and second human eyes and wherein the means for computing the profile includes means for pre-determining a model of the eye-to-eye profile and means for determining an actual profile from the image and computing a goodness-of-fit between the actual profile and the model profile.
Claim 145
Dependent Claim
46 words
The system as in claim 131, wherein the first and second objects are first and second human eyes and wherein the means for computing the symmetry includes means for computing a symmetry between first and second halves of a face window determined by the eye locations.
Claim 146
Dependent Claim
46 words
The system as in claim 131, wherein the first and second objects are first and second human eyes and wherein the means for computing the evidence of mouth includes means for computing strength and orientation of edges within a mouth window determined by the eye locations.
Claim 147
Dependent Claim
18 words
The system as in claim 128 further comprising means for normalizing the template for maximizing robustness of matching.
Claim 148
Dependent Claim
24 words
The system as in claim 128 further comprising the step of creating a image block of the same size and orientation as the template.
Claim 149
Dependent Claim
19 words
The system as in claim 140 further comprising means for normalizing the image block for maximizing robustness of matching.
Claim 150
Dependent Claim
30 words
The system as in claim 140 further comprising means for extracting individual sub-zones in both the template and the image block, and means for performing cross-correlation for each corresponding sub-zone.
Claim 151
Dependent Claim
29 words
The system as in claim 140 further comprising means for computing the overall cross-correlation score for the image block if the cross-correlation score for each sub-zone exceeds a threshold.
Claim 152
Dependent Claim
19 words
The system as in claim 128 further comprising means for identifying the locations that give locally maximum cross-correlation score.
Claim 153
Independent Claim
207 words
A system for locating first and second objects each having substantially the same physical characteristics, and the ratio of the distance between the first and second objects and the size of each object is substantially invariant, the method comprising the steps of: (a) means for displaying a digital image on a graphical user interface; (b) means for inputting to the interface an approximate position of each object for forming initial input positions; (c) means for determining an estimate orientation of each object based on an angle derived from the initial input positions of the first and second objects; (d) means for determining an estimate size of each object based on the distance obtained from the initial input positions of the first and second objects; (e) means for forming a searching window for the first object; the center of the window is determined by the input position of the first object and the size of the window is determined by the estimate size of the first object; (f) means for reiteratively positioning a template on the search window for determining a location that gives a desired match of the first object relative to the template; and (g) means for repeating steps (e) and (f) for the second object.
Claim 154
Independent Claim
207 words
A system for locating first and second objects each having substantially the same physical characteristics, and the ratio of the distance between the first and second objects and the size of each object is substantially invariant, the method comprising the steps of: (a) means for displaying a digital image on a graphical user interface; (b) means for inputting to the interface an approximate position of each object for forming initial input positions; (c) means for determining an estimate orientation of each object based on an angle derived from the initial input positions of the first and second objects; (d) means for determining an estimate size of each object based on the distance obtained from the initial input positions of the first and second objects; (e) means for forming a searching window for the first object; the center of the window is determined by the input position of the first object and the size of the window is determined by the estimate size of the first object; (f) means for reiteratively positioning a template on the search window for determining a location that gives a desired match of the first object relative to the template; and (g) means for repeating steps (e) and (f) for the second object.
Claim 155
Dependent Claim
30 words
The system as in claim 145, further comprising the step of (h) determining a plurality of locations in each search window that give a desired matching response to the template.
Claim 156
Dependent Claim
30 words
The system as in claim 146 further comprising means for finding the best pair of locations from all possible combinations of identified locations of both the first and second objects.
Claim 157
Dependent Claim
41 words
The system as in claim 147, wherein the means for finding best pair of locations includes means for computing a plurality of figures of merit and means for determining a pair of locations that give a best combined figure of merit.
Claim 158
Dependent Claim
38 words
The system as in claim 148, wherein the means for computing a plurality of figures of merit includes means for computing individually or in combination an orientation, proximity, combined correlation score, proportion, profile, symmetry or evidence of mouth.
Claim 159
Dependent Claim
49 words
The system as in claim 149, wherein the first and second objects are first and second human eyes and wherein computing an orientation includes measuring the difference between the orientation of the line connecting the first and second eyes, and the average orientation of the first and second eyes.
Claim 160
Dependent Claim
30 words
The system as in claim 149, wherein the means for computing a proximity includes means for measuring proximity of the first and second objects to the initial input positions, respectively.
Claim 161
Dependent Claim
31 words
The system as in claim 149, wherein the means for computing a combined correlation score includes means for summing up the individual correlation scores obtained from the matching obtained in (e).
Claim 162
Dependent Claim
44 words
The system as in claim 149, wherein the first and second objects are first and second human eyes and wherein the means for computing a proportion includes means for computing a distance between the first and second eyes for satisfying an anthropological prior model.
Claim 163
Dependent Claim
58 words
The system as in claim 149, wherein the first and second objects are first and second human eyes and wherein the means for computing the profile includes means for predetermining a model of the eye-to-eye profile and means for determining an actual profile from the image and computing a goodness-of-fit between the actual profile and the model profile.
Claim 164
Dependent Claim
41 words
The system as in claim 149, wherein the first and second objects are first and second human eyes and wherein computing the symmetry includes computing a symmetry between first and second halves of a face window determined by the eye locations.
Claim 165
Dependent Claim
41 words
The system as in claim 149, wherein the first and second objects are first and second human eyes and wherein computing the evidence of mouth includes computing strength and orientation of edges within a mouth window determined by the eye locations.
Claim 166
Dependent Claim
18 words
The system as in claim 146 further comprising means for normalizing the template for maximizing robustness of matching.
Claim 167
Dependent Claim
24 words
The system as in claim 146 further comprising the step of creating a image block of the same size and orientation as the template.
Claim 168
Dependent Claim
19 words
The system as in claim 158 further comprising means for normalizing the image block for maximizing robustness of matching.
Claim 169
Dependent Claim
28 words
The system as in claim 158 further comprising means for extracting individual sub-zones in both the template and the image block, and performing cross-correlation for each corresponding sub-zone.
Claim 170
Dependent Claim
30 words
The system as in claim 158 further comprising the step of computing the overall cross-correlation score for the image block if the cross-correlation score for each sub-zone exceeds a threshold.
Claim 171
Dependent Claim
19 words
The system as in claim 146 further comprising means for identifying the locations that give locally maximum cross-correlation score.
Claim 172
Independent Claim
255 words
A system for locating first and second objects in an image each object having substantially the same physical characteristics, and the ratio of the distance between the first and second objects and the size of each object is substantially invariant, the method comprising the steps of: (a) means for displaying a digital image on a graphical user interface; (b) means for estimating an approximate position of each object for forming initial input positions based on a format of the image; (c) means for determining an estimate size of each object based on the distance obtained from the initial input positions of the first and second objects; (d) means for forming a first searching window for the first object; the center of the first window is determined by the input position of the first object and the size of the first window is determined by the estimate size of the first object; (e) means for reiteratively positioning a template on the first search window for determining a location that gives a desired match of the first object relative to the template; (f) means for forming a second searching window for the second object; the center of the second window is determined by the input position of the second object and the size of the second window is determined by the estimate size of the second object; and (g) means for reiteratively positioning a template on the second search window for determining a location that gives a desired match of the second object relative to the template.
Claim 173
Independent Claim
255 words
A system for locating first and second objects in an image each object having substantially the same physical characteristics, and the ratio of the distance between the first and second objects and the size of each object is substantially invariant, the method comprising the steps of: (a) means for displaying a digital image on a graphical user interface; (b) means for estimating an approximate position of each object for forming initial input positions based on a format of the image; (c) means for determining an estimate size of each object based on the distance obtained from the initial input positions of the first and second objects; (d) means for forming a first searching window for the first object; the center of the first window is determined by the input position of the first object and the size of the first window is determined by the estimate size of the first object; (e) means for reiteratively positioning a template on the first search window for determining a location that gives a desired match of the first object relative to the template; (f) means for forming a second searching window for the second object; the center of the second window is determined by the input position of the second object and the size of the second window is determined by the estimate size of the second object; and (g) means for reiteratively positioning a template on the second search window for determining a location that gives a desired match of the second object relative to the template.
Claim 174
Dependent Claim
29 words
The system as in claim 163, further comprising (h) means for determining a plurality of locations in each search window that give a desired matching response to the template.
Claim 175
Dependent Claim
30 words
The system as in claim 164 further comprising means for finding the best pair of locations from all possible combinations of identified locations of both the first and second objects.
Claim 176
Dependent Claim
41 words
The system as in claim 165, wherein the means for finding best pair of locations includes means for computing a plurality of figures of merit and means for determining a pair of locations that give a best combined figure of merit.
Claim 177
Dependent Claim
38 words
The system as in claim 166, wherein the means for computing a plurality of figures of merit includes means for computing individually or in combination an orientation, proximity, combined correlation score, proportion, profile, symmetry or evidence of mouth.
Claim 178
Dependent Claim
54 words
The system as in claim 167, wherein the first and second objects are first and second human eyes and wherein the means for computing an orientation includes means for measuring the difference between the orientation of the line connecting the first and second eyes, and the average orientation of the first and second eyes.
Claim 179
Dependent Claim
28 words
The system as in claim 167, wherein the means for computing a proximity includes measuring proximity of the first and second objects to the initial input positions, respectively.
Claim 180
Dependent Claim
26 words
The system as in claim 167, wherein computing a combined correlation score includes summing up the individual correlation scores obtained from the matching obtained in (e).
Claim 181
Dependent Claim
44 words
The system as in claim 167, wherein the first and second objects are first and second human eyes and wherein the means for computing a proportion includes means for computing a distance between the first and second eyes for satisfying an anthropological prior model.
Claim 182
Dependent Claim
60 words
The system as in claim 167, wherein the first and second objects are first and second human eyes and wherein the means for computing the profile includes means for pre-determining a model of the eye-to-eye profile and means for determining an actual profile from the image and means for computing a goodness-of-fit between the actual profile and the model profile.
Claim 183
Dependent Claim
46 words
The system as in claim 167, wherein the first and second objects are first and second human eyes and wherein the means for computing the symmetry includes means for computing a symmetry between first and second halves of a face window determined by the eye locations.
Claim 184
Dependent Claim
46 words
The system as in claim 167, wherein the first and second objects are first and second human eyes and wherein the means for computing the evidence of mouth includes means for computing strength and orientation of edges within a mouth window determined by the eye locations.
Claim 185
Dependent Claim
18 words
The system as in claim 164 further comprising means for normalizing the template for maximizing robustness of matching.
Claim 186
Dependent Claim
23 words
The system as in claim 164 further comprising means for creating a image block of the same size and orientation as the template.
Claim 187
Dependent Claim
19 words
The system as in claim 176 further comprising means for normalizing the image block for maximizing robustness of matching.
Claim 188
Dependent Claim
28 words
The system as in claim 176 further comprising means for extracting individual sub-zones in both the template and the image block, and performing cross-correlation for each corresponding sub-zone.
Claim 189
Dependent Claim
29 words
The system as in claim 176 further comprising means for computing the overall cross-correlation score for the image block if the cross-correlation score for each sub-zone exceeds a threshold.
Claim 190
Dependent Claim
20 words
The system as in claim 164 further comprising the step of identifying the locations that give locally maximum cross-correlation score.
Claim 191
Independent Claim
242 words
A system for locating first and second objects each having substantially the same physical characteristics, and the ratio of the distance between the first and second objects and the size of each object is substantially invariant, the system comprising: (a) means for displaying a digital image on a graphical user interface; (b) means for estimating an approximate position of each object for forming initial input positions; (c) means for determining an estimate orientation of each object based on an angle derived from the initial input positions of the first and second objects; (d) means for forming a first searching window for the first object; the center of the first window is determined by the initial input position of the first object and the size of the first window is determined by the estimate size of the first object; (e) means for reiteratively positioning a template on the first search window for determining a location that gives a desired match of the first object relative to the template; and (f) means for forming a second searching window for the first object; the center of the second window is determined by the input position of the first object and the size of the second window is determined by the estimate size of the first object; (g) means for reiteratively positioning a template on the second search window for determining a location that gives a desired match of the first object relative to the template.
Claim 192
Independent Claim
242 words
A system for locating first and second objects each having substantially the same physical characteristics, and the ratio of the distance between the first and second objects and the size of each object is substantially invariant, the system comprising: (a) means for displaying a digital image on a graphical user interface; (b) means for estimating an approximate position of each object for forming initial input positions; (c) means for determining an estimate orientation of each object based on an angle derived from the initial input positions of the first and second objects; (d) means for forming a first searching window for the first object; the center of the first window is determined by the initial input position of the first object and the size of the first window is determined by the estimate size of the first object; (e) means for reiteratively positioning a template on the first search window for determining a location that gives a desired match of the first object relative to the template; and (f) means for forming a second searching window for the first object; the center of the second window is determined by the input position of the first object and the size of the second window is determined by the estimate size of the first object; (g) means for reiteratively positioning a template on the second search window for determining a location that gives a desired match of the first object relative to the template.
Claim 193
Dependent Claim
24 words
The system as in claim 181 further comprising means for determining a plurality of locations that give a desired matching response to the template.
Claim 194
Dependent Claim
31 words
The system as in claim 181 further comprising the step of finding the best pair of locations from all possible combinations of identified locations of both the first and second objects.
Claim 195
Dependent Claim
39 words
The system as in claim 183, wherein the means for finding best pair of locations includes means for computing a plurality of figures of merit and determining a pair of locations that give a best combined figure of merit.
Claim 196
Dependent Claim
38 words
The system as in claim 184, wherein the means for computing a plurality of figures of merit includes means for computing individually or in combination an orientation, proximity, combined correlation score, proportion, profile, symmetry or evidence of mouth.
Claim 197
Dependent Claim
54 words
The method as in claim 185, wherein the first and second objects are first and second human eyes and wherein the means for computing an orientation includes means for measuring the difference between the orientation of the line connecting the first and second eyes, and the average orientation of the first and second eyes.
Claim 198
Dependent Claim
30 words
The system as in claim 185, wherein the means for computing a proximity includes means for measuring proximity of the first and second objects to the initial input positions, respectively.
Claim 199
Dependent Claim
31 words
The system as in claim 185, wherein the means for computing a combined correlation score includes means for summing up the individual correlation scores obtained from the matching obtained in (e).
Claim 200
Dependent Claim
44 words
The system as in claim 185, wherein the first and second objects are first and second human eyes and wherein the means for computing a proportion includes means for computing a distance between the first and second eyes for satisfying an anthropological prior model.
Claim 201
Dependent Claim
58 words
The system as in claim 185, wherein the first and second objects are first and second human eyes and wherein the means for computing the profile includes means for pre-determining a model of the eye-to-eye profile and means for determining an actual profile from the image and computing a goodness-of-fit between the actual profile and the model profile.
Claim 202
Dependent Claim
46 words
The system as in claim 185, wherein the first and second objects are first and second human eyes and wherein the means for computing the symmetry includes means for computing a symmetry between first and second halves of a face window determined by the eye locations.
Claim 203
Dependent Claim
46 words
The system as in claim 185, wherein the first and second objects are first and second human eyes and wherein the means for computing the evidence of mouth includes means for computing strength and orientation of edges within a mouth window determined by the eye locations.
Claim 204
Dependent Claim
18 words
The system as in claim 182 further comprising means for normalizing the template for maximizing robustness of matching.
Claim 205
Dependent Claim
23 words
The system as in claim 182 further comprising means for creating a image block of the same size and orientation as the template.
Claim 206
Dependent Claim
19 words
The system as in claim 194 further comprising means for normalizing the image block for maximizing robustness of matching.
Claim 207
Dependent Claim
28 words
The system as in claim 195 further comprising means for extracting individual sub-zones in both the template and the image block, and performing cross-correlation for each corresponding sub-zone.
Claim 208
Dependent Claim
29 words
The system as in claim 195 further comprising means for computing the overall cross-correlation score for the image block if the cross-correlation score for each sub-zone exceeds a threshold.
Claim 209
Dependent Claim
19 words
The system as in claim 183 further comprising means for identifying the locations that give locally maximum cross-correlation score.
Claim 210
Independent Claim
212 words
A system for locating first and second objects in an image each object having substantially the same physical characteristics, and the ratio of the distance between the first and second objects and the size of each object is substantially invariant, the system comprising: (a) means for displaying a digital image on a graphical user interface; (b) means for estimating an approximate position of each object for forming initial input positions based on a format of the image; (c) means for determining an estimate orientation of each object based on an angle derived from the initial input positions of the first and second objects; (d) means for determining an estimate size of each object based on the distance obtained from the initial input positions of the first and second objects; (e) means for forming a searching window for the first object; the center of the window is determined by the input position of the first object and the size of the window is determined by the estimate size of the first object; (f) means for reiteratively positioning a template on the search window for determining a location that gives a desired match of the first object relative to the template; and (g) means for repeating steps (e) and (f) for the second object.
Claim 211
Independent Claim
212 words
A system for locating first and second objects in an image each object having substantially the same physical characteristics, and the ratio of the distance between the first and second objects and the size of each object is substantially invariant, the system comprising: (a) means for displaying a digital image on a graphical user interface; (b) means for estimating an approximate position of each object for forming initial input positions based on a format of the image; (c) means for determining an estimate orientation of each object based on an angle derived from the initial input positions of the first and second objects; (d) means for determining an estimate size of each object based on the distance obtained from the initial input positions of the first and second objects; (e) means for forming a searching window for the first object; the center of the window is determined by the input position of the first object and the size of the window is determined by the estimate size of the first object; (f) means for reiteratively positioning a template on the search window for determining a location that gives a desired match of the first object relative to the template; and (g) means for repeating steps (e) and (f) for the second object.
Claim 212
Dependent Claim
29 words
The system as in claim 199, further comprising (h) means for determining a plurality of locations in each search window that give a desired matching response to the template.
Claim 213
Dependent Claim
30 words
The system as in claim 200 further comprising means for finding the best pair of locations from all possible combinations of identified locations of both the first and second objects.
Claim 214
Dependent Claim
39 words
The system as in claim 201, wherein the means for finding best pair of locations includes means for computing a plurality of figures of merit and determining a pair of locations that give a best combined figure of merit.
Claim 215
Dependent Claim
38 words
The system as in claim 201, wherein the means for computing a plurality of figures of merit includes means for computing individually or in combination an orientation, proximity, combined correlation score, proportion, profile, symmetry or evidence of mouth.
Claim 216
Dependent Claim
54 words
The system as in claim 203, wherein the first and second objects are first and second human eyes and wherein the means for computing an orientation includes means for measuring the difference between the orientation of the line connecting the first and second eyes, and the average orientation of the first and second eyes.
Claim 217
Dependent Claim
30 words
The system as in claim 203, wherein the means for computing a proximity includes means for measuring proximity of the first and second objects to the initial input positions, respectively.
Claim 218
Dependent Claim
31 words
The system as in claim 203, wherein the means for computing a combined correlation score includes means for summing up the individual correlation scores obtained from the matching obtained in (e).
Claim 219
Dependent Claim
44 words
The system as in claim 203, wherein the first and second objects are first and second human eyes and wherein the means for computing a proportion includes means for computing a distance between the first and second eyes for satisfying an anthropological prior model.
Claim 220
Dependent Claim
58 words
The system as in claim 203, wherein the first and second objects are first and second human eyes and wherein the means for computing the profile includes means for pre-determining a model of the eye-to-eye profile and means for determining an actual profile from the image and computing a goodness-of-fit between the actual profile and the model profile.
Claim 221
Dependent Claim
46 words
The system as in claim 203, wherein the first and second objects are first and second human eyes and wherein the means for computing the symmetry includes means for computing a symmetry between first and second halves of a face window determined by the eye locations.
Claim 222
Dependent Claim
45 words
The system in claim 203, wherein the first and second objects are first and second human eyes and wherein the means for computing the evidence of mouth includes means for computing strength and orientation of edges within a mouth window determined by the eye locations.
Claim 223
Dependent Claim
18 words
The system as in claim 200 further comprising means for normalizing the template for maximizing robustness of matching.
Claim 224
Dependent Claim
23 words
The system as in claim 200 further comprising means for creating a image block of the same size and orientation as the template.
Claim 225
Dependent Claim
19 words
The system as in claim 212 further comprising means for normalizing the image block for maximizing robustness of matching.
Claim 226
Dependent Claim
28 words
The system as in claim 212 further comprising means for extracting individual sub-zones in both the template and the image block, and performing cross-correlation for each corresponding sub-zone.
Claim 227
Dependent Claim
29 words
The system as in claim 212 further comprising means for computing the overall cross-correlation score for the image block if the cross-correlation score for each sub-zone exceeds a threshold.
Claim 228
Dependent Claim
19 words
The system as in claim 200 further comprising means for identifying the locations that give locally maximum cross-correlation score.
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USPTO Annuity & Maintenance Windows
| Annuity Stage | Window Opens | Payment Deadline | Surcharge Period Until | Estimated Fee | Status |
|---|---|---|---|---|---|
| 3.5 Years (Year 4) | 2003-06-06 | 2003-12-06 | 2004-06-06 | $2000.00 | Window Closed / Lapsed |
| 7.5 Years (Year 8) | 2007-06-06 | 2007-12-06 | 2008-06-06 | $3760.00 | Window Closed / Lapsed |
| 11.5 Years (Year 12) | 2011-06-06 | 2011-12-06 | 2012-06-06 | $7700.00 | Window Closed / Lapsed |