US5793900A
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Generating categorical depth maps using passive defocus sensing
Assignee: Leland Stanford Junior University
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Filing: 1995-12-29
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Granted: 1998-08-11
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Expires: 2015-12-29
Abstract
Abstract A method is disclosed for generating a categorical depth map of a scene using passive defocus sensing. In a preferred embodiment three synchronized CCD cameras focused at different distances detect three images of the same scene. An image processor partitions the images into an array of regions and calculates a sharpness value for each region. The sharpness value for a region is calculated by summing over all pixels (x,y) in the region the absolute difference in the intensity value of a pixel (x,y)( with pixel (x-k,y-l), where k and l are constants. The image processor then constructs a depth map of the scene by determining for each region the image with the greatest sharpness in that region. An application of the invention to a mobile robot control system is described in detail. Among other applications, the method may be used for collision avoidance, object detection, and speed measurement.
Inventors
- 👤 Illah Reza Nourbakhsh
- 👤 David Andre
Bibliographic Details
Application Number
—
Jurisdiction
US
Data Source
google_patents
Last Synchronized
2026-11-09 17:58
CPC Classifications
G; G06; G06T; G06T7/00; G06T7/50; G06T7/55; G06T7/571; H; H04; H04N; H04N13/00; H04N13/20; H04N13/204; H04N13/207; H04N13/236; H04N13/271; G06T2207/00; G06T2207/10; G06T2207/10004; G06T2207/10012; G06T2207/10141; G06T2207/10148; G06T2207/20; G06T2207/20021
Claims Analysis
Total Claims: 23
Claim 1
Independent Claim
166 words
A method for generating a categorical depth map of a scene, the depth map comprising m depth map regions, where m≧1, the method comprising the steps of: detecting n images of the scene using n cameras focused at different distances, where n>1; dividing each of the n images into m predetermined two-dimensional image regions such that each depth map region corresponds to n similar image regions taken from the n images; determining a sharpness value for each region of the m image regions in each image of the n images; identifying, for each depth map region, an image number of a sharpest image selected from the n similar image regions taken from the n images, wherein the sharpest image has a maximal sharpness value; and assigning a categorical depth value to each depth map region of the m depth map regions, where the depth value for a depth map region is determined from an image number of the sharpest image identified for the depth map region.
Claim 2
Independent Claim
166 words
A method for generating a categorical depth map of a scene, the depth map comprising m depth map regions, where m≧1, the method comprising the steps of: detecting n images of the scene using n cameras focused at different distances, where n>1; dividing each of the n images into m predetermined two-dimensional image regions such that each depth map region corresponds to n similar image regions taken from the n images; determining a sharpness value for each region of the m image regions in each image of the n images; identifying, for each depth map region, an image number of a sharpest image selected from the n similar image regions taken from the n images, wherein the sharpest image has a maximal sharpness value; and assigning a categorical depth value to each depth map region of the m depth map regions, where the depth value for a depth map region is determined from an image number of the sharpest image identified for the depth map region.
Claim 3
Dependent Claim
25 words
The method of claim 1 further comprising the step of synchronizing the n cameras so that they simultaneously detect the n images of the scene.
Claim 4
Dependent Claim
29 words
The method of claim 1 further comprising the step of orienting the n cameras so that the n images represent very similar but slightly different perspectives of the scene.
Claim 5
Dependent Claim
28 words
The method of claim 1 further comprising the step of using at least one beamsplitter to ensure that the n cameras view the scene from the same perspective.
Claim 6
Dependent Claim
61 words
The method of claim 1 wherein the step of determining a sharpness value for each region of the m image regions comprises: finding, for each pixel in the region, the absolute difference between the intensity value of the pixel and the intensity value of a nearby pixel; and summing together the absolute differences found for all the pixels in the region.
Claim 7
Dependent Claim
35 words
The method of claim 5 wherein the nearby pixel is a pixel horizontally displaced by k pixels and vertically displaced by l pixels, where k and l are integers, one of which is not zero.
Claim 8
Dependent Claim
38 words
The method of claim 1 wherein the step of assigning a categorical depth value to each depth map region comprises finding among the n image regions corresponding the depth map region a region having a maximal sharpness value.
Claim 9
Independent Claim
150 words
A device for producing a categorical depth map of a scene, the depth map comprising m depth map regions, where m≧2, the device comprising: n camera means for detecting n images of the scene, where the n camera means are focused at different distances, where n>1; image processing means for dividing each of the n images into m predetermined two-dimensional image regions such that each depth map region corresponds to n similar image regions taken from the n images, and for determining a sharpness value for each region of the m image regions in each image of the n images; comparing means for assigning a categorical depth value to each depth map region of the m depth map regions, where the depth value for a depth map region is determined from an image number of a sharpest image selected from the n similar image regions taken from the n images.
Claim 10
Independent Claim
150 words
A device for producing a categorical depth map of a scene, the depth map comprising m depth map regions, where m≧2, the device comprising: n camera means for detecting n images of the scene, where the n camera means are focused at different distances, where n>1; image processing means for dividing each of the n images into m predetermined two-dimensional image regions such that each depth map region corresponds to n similar image regions taken from the n images, and for determining a sharpness value for each region of the m image regions in each image of the n images; comparing means for assigning a categorical depth value to each depth map region of the m depth map regions, where the depth value for a depth map region is determined from an image number of a sharpest image selected from the n similar image regions taken from the n images.
Claim 11
Dependent Claim
30 words
The device of claim 8 further comprising a synch means for synchronizing the n camera means with each other so that they simultaneously detect the n images of the scene.
Claim 12
Dependent Claim
27 words
The device of claim 8 wherein the n camera means are oriented so that the n images represent very similar but slightly different perspectives of the scene.
Claim 13
Dependent Claim
24 words
The device of claim 8 further comprising a beam splitting means for ensuring that the n cameras view the scene from the same perspective.
Claim 14
Dependent Claim
22 words
The device of claim 8 further comprising a filtering means for reducing the intensity of light detected by the n camera means.
Claim 15
Dependent Claim
58 words
The device of claim 8 wherein the image processing means comprises a first means for finding, for each pixel in the region, the absolute difference between the intensity value of the pixel and the intensity value of a nearby pixel; and a second means for summing together the absolute differences found for all the pixels in the region.
Claim 16
Dependent Claim
35 words
The device of claim 13 wherein the nearby pixel is a pixel horizontally displaced by k pixels and vertically displaced by l pixels, where k and l are integers, one of which is not zero.
Claim 17
Dependent Claim
31 words
The device of claim 8 wherein the comparing means comprises a means for finding, among the n image regions corresponding the depth map region, a region having a maximal sharpness value.
Claim 18
Dependent Claim
23 words
The device of claim 8 further comprising n intensity control means for controlling the amount of light detected by the n camera means.
Claim 19
Dependent Claim
13 words
The device of claim 8 used for detecting the presence of an object.
Claim 20
Dependent Claim
13 words
The device of claim 8 used for detecting the speed of an object.
Claim 21
Dependent Claim
12 words
The device of claim 8 used to assist a visually impaired person.
Claim 22
Dependent Claim
123 words
A mobile robot comprising: n camera means for detecting n images, where the camera means are focused at different distances; image processing means for dividing each of the n images into m predetermined two-dimensional image regions such that n similar image regions taken from the n images are in correspondence with each other, and for determining a sharpness value for each image region in each image, where the sharpness value is given by the formula ##EQU2## comparing means for generating a depth map by comparing the sharpness value of each region with the sharpness value of a corresponding similar region in another image; and motion control means for controlling the movement of a robot in response to information contained in the depth map.
Claim 23
Dependent Claim
123 words
A mobile robot comprising: n camera means for detecting n images, where the camera means are focused at different distances; image processing means for dividing each of the n images into m predetermined two-dimensional image regions such that n similar image regions taken from the n images are in correspondence with each other, and for determining a sharpness value for each image region in each image, where the sharpness value is given by the formula ##EQU2## comparing means for generating a depth map by comparing the sharpness value of each region with the sharpness value of a corresponding similar region in another image; and motion control means for controlling the movement of a robot in response to information contained in the depth map.
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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) | 2001-08-10 | 2002-02-09 | 2002-08-11 | $2000.00 | Window Closed / Lapsed |
| 7.5 Years (Year 8) | 2005-08-10 | 2006-02-09 | 2006-08-11 | $3760.00 | Window Closed / Lapsed |
| 11.5 Years (Year 12) | 2009-08-10 | 2010-02-09 | 2010-08-11 | $7700.00 | Window Closed / Lapsed |