Technique for tracking objects through a series of images

Claim 3

The method as defined in claim 1 , wherein the step of matching each identified grouping of substantially adjacent pixels in the first representation with an identified grouping of substantially adjacent pixels in the second representation includes the step of: calculating a score between each identified grouping of substantially adjacent pixels in the first representation and each identified grouping of substantially adjacent pixels in the second representation.

Claim 4

The method as defined in claim 2 , wherein said step of calculating a score between each identified grouping of substantially adjacent pixels in the first representation and each identified grouping of substantially adjacent pixels in the second representation includes the step of: calculating a score based upon a size comparison of each identified grouping of substantially adjacent pixels in the first representation and each identified grouping of substantially adjacent pixels in the second representation.

Claim 5

The method as defined in claim 2 , wherein said step of calculating a score between each identified grouping of substantially adjacent pixels in the first representation and each identified grouping of substantially adjacent pixels in the second representation includes the step of: calculating a score based upon a location comparison of each identified grouping of substantially adjacent pixels within the first representation and each identified grouping of substantially adjacent pixels within the second representation.

Claim 6

The method as defined in claim 2 , wherein said step of calculating a score between each identified grouping of substantially adjacent pixels in the first representation and each identified grouping of substantially adjacent pixels in the second representation includes the step of: calculating a score based upon an aspect ratio comparison of each identified grouping of substantially adjacent pixels in the representation and each identified grouping of substantially adjacent pixels in the second representation.

Claim 7

The method as defined in claim 2 , wherein said step of calculating a score between each identified grouping of substantially adjacent pixels in the first representation and each identified grouping of substantially adjacent pixels in the second representation includes the step of: calculating a score based upon a texture comparison of each identified grouping of substantially adjacent pixels in the first representation and each identified grouping of substantially adjacent pixels in the second representation.

Claim 8

The method as defined in claim 2 , wherein said step of calculating a score between each identified grouping of substantially adjacent pixels in the first representation and each identified grouping of substantially adjacent pixels in the second representation includes the step of: calculating a score based upon a velocity comparison of each identified grouping of substantially adjacent pixels in the first representation and each identified grouping of substantially adjacent pixels in the second representation.

Claim 9

The method as defined in claim 2 , wherein said step of calculating a score between each identified grouping of substantially adjacent pixels in the first representation and each identified grouping of substantially adjacent pixels in the second representation includes the step of: calculating a score based upon a color comparison of each identified grouping of substantially adjacent pixels in the first representation and each identified grouping of substantially adjacent pixels in the second representation.

Claim 10

The method as defined in claim 8 , wherein the first representation represents differences between a third representation of a plurality of pixels and a fourth representation of a plurality of pixels, wherein second representation represents differences between a fifth representation of a plurality of pixels and the fourth representation of a plurality of pixels, wherein the step of calculating a score based upon a color comparison of each identified grouping of substantially adjacent pixels in the first representation and each identified grouping of substantially adjacent pixels in the second representation includes the steps of: color sampling pixel areas in the third and the fifth representations corresponding to pixel areas in each identified grouping of substantially adjacent pixels in the first and the second representations; averaging the color sampled pixel areas; and comparing the averaged color sampled pixel areas.

Claim 11

The method as defined in claim 9 , wherein the step of color sampling pixel areas in the third and the fifth representations corresponding to pixel areas in each identified grouping of substantially adjacent pixels in the first and the second representations includes the step of: color sampling pixel areas in a predefined pattern in the third and the fifth representations.

Claim 12

The method as defined in claim 9 , further comprising the step of: combining a subset of the compared averaged color sampled pixel areas to provide a measure of color accuracy.

Claim 13

The method as defined in claim 2 , further comprising the step of: comparing each score between each identified grouping of substantially adjacent pixels in the first representation and each identified grouping of substantially adjacent pixels in the second representation to a threshold value.

Claim 14

The method as defined in claim 12 , further comprising the steps of: listing each score between each identified grouping of substantially adjacent pixels in the first representation and each identified grouping of substantially adjacent pixels in the second representation according to a score value; matching an identified grouping of substantially adjacent pixels in the first representation and an identified grouping of substantially adjacent pixels in the second representation according to highest score values; and removing the matched identified groupings from the listing.

Claim 15

The method as defined in claim 13 , further comprising the step of: tracking the matched identified groupings through the series of images.

Claim 18

The apparatus as defined in claim 15 , wherein the matcher includes a calculator for calculating a score between each identified grouping of substantially adjacent pixels in the first representation and each identified grouping of substantially adjacent pixels in the second representation.

Claim 19

The apparatus as defined in claim 16 , wherein the calculator calculates a score based upon a size comparison of each identified grouping of substantially adjacent pixels in the first representation and each identified grouping of substantially adjacent pixels in the second representation.

Claim 20

The apparatus as defined in claim 16 , wherein the calculator calculates a score based upon a location comparison of each identified grouping of substantially adjacent pixels within the first representation and each identified grouping of substantially adjacent pixels within the second representation.

Claim 21

The apparatus as defined in claim 16 , wherein the calculator calculates a score based upon an aspect ratio comparison of each identified grouping of substantially adjacent pixels in the representation and each identified grouping of substantially adjacent pixels in the second representation.

Claim 22

The apparatus as defined in claim 16 , wherein the calculator calculates a score based upon a texture comparison of each identified grouping of substantially adjacent pixels in the representation and each identified grouping of substantially adjacent pixels in the second representation.

Claim 23

The apparatus as defined in claim 16 , wherein the calculator calculates a score based upon a velocity comparison of each identified grouping of substantially adjacent pixels in the first representation and each identified grouping of substantially adjacent pixels in the second representation.

Claim 24

The apparatus as defined in claim 16 , wherein the calculator calculates a score based upon a color comparison of each identified grouping of substantially adjacent pixels in the first representation and each identified grouping of substantially adjacent pixels in the second representation.

Claim 25

The apparatus as defined in claim 22 , wherein the first representation represents differences between a third representation of a plurality of pixels and a fourth representation of a plurality of pixels, wherein second representation represents differences between a fifth representation of a plurality of pixels and the fourth representation of a plurality of pixels, wherein the calculator includes: a sampler for color sampling pixel areas in the third and the fifth representations corresponding to pixel areas in each identified grouping of substantially adjacent pixels in the first and the second representations; an averager for averaging the color sampled pixel areas; and a comparer for comparing the averaged color sampled pixel areas.

Claim 26

The apparatus as defined in claim 23 , wherein the sampler color samples pixel areas in a predefined pattern in the third and the fifth representations.

Claim 27

The apparatus as defined in claim 23 , further comprising: a combiner for combining a subset of the compared averaged color sampled pixel areas to provide a measure of color accuracy.

Claim 28

The apparatus as defined in claim 16 , further comprising: a comparer for comparing each score between each identified grouping of substantially adjacent pixels in the first representation and each identified grouping of substantially adjacent pixels in the second representation to a threshold value.

Claim 29

The apparatus as defined in claim 26 , further comprising: a lister for listing each score between each identified grouping of substantially adjacent pixels in the first representation and each identified grouping of substantially adjacent pixels in the second representation according to a score value; a matcher for matching an identified grouping of substantially adjacent pixels in the first representation and an identified grouping of substantially adjacent pixels in the second representation according to highest score values; and a remover for removing the matched identified groupings from the listing.

Claim 30

The apparatus as defined in claim 27 , further comprising: a tracker for tracking the matched identified groupings through the series of images.

Claim 31

An article of manufacture for tracking objects through a series of images, wherein each image includes a plurality of pixels, and wherein each pixel is defined by digitized intensity and digitized color, the apparatus comprising: a computer readable storage medium; and computer programming stored on the storage medium; wherein, the stored computer programming is configured to be readable from the computer readable storage medium by a computer and thereby cause the computer to operate so as to: establish a background image of an entire background image containing no objects of interest by averaging a plurality of images of entire scenes, store the averaged background image as a plurality of pixels, a first and a second representation of the images' plurality of pixels, process the digitized intensity and digitized color of each pixel, with respect to the stored averaged background image pixels, group substantially adjacent pixels according to their processed intensity and their processed color, thereby forming at least one first identified grouping of substantially adjacent pixels within the first representation and at least one second grouping of substantially adjacent pixels within the second representation, match the first and second groupings of substantially adjacent pixels thereby defining an identified grouping of substantially adjacent pixels, determine if the identified grouping is a grouping of interest, and updating the averaged background image by averaging in the pixels from the first and the second representations minus any identified grouping of interest.

Claim 32

An article of manufacture for tracking objects through a series of images, wherein each image includes a plurality of pixels, and wherein each pixel is defined by digitized intensity and digitized color, the apparatus comprising: a computer readable storage medium; and computer programming stored on the storage medium; wherein, the stored computer programming is configured to be readable from the computer readable storage medium by a computer and thereby cause the computer to operate so as to: establish a background image of an entire background image containing no objects of interest by averaging a plurality of images of entire scenes, store the averaged background image as a plurality of pixels, a first and a second representation of the images' plurality of pixels, process the digitized intensity and digitized color of each pixel, with respect to the stored averaged background image pixels, group substantially adjacent pixels according to their processed intensity and their processed color, thereby forming at least one first identified grouping of substantially adjacent pixels within the first representation and at least one second grouping of substantially adjacent pixels within the second representation, match the first and second groupings of substantially adjacent pixels thereby defining an identified grouping of substantially adjacent pixels, determine if the identified grouping is a grouping of interest, and updating the averaged background image by averaging in the pixels from the first and the second representations minus any identified grouping of interest.

Claim 33

The article of manufacture as defined in claim 29 , further causing the computer to operate so as to: calculate a score between each identified grouping of substantially adjacent pixels in the first representation and each identified grouping of substantially adjacent pixels in the second representation.

Claim 34

The article of manufacture as defined in claim 30 , further causing the computer to operate so as to: calculate a score based upon a size comparison of each identified grouping of substantially adjacent pixels in the first representation and each identified grouping of substantially adjacent pixels in the second representation.

Claim 35

The article of manufacture as defined in claim 30 , further causing the computer to operate so as to: calculate a score based upon a location comparison of each identified grouping of substantially adjacent pixels within the first representation and each identified grouping of substantially adjacent pixels within the second representation.

Claim 36

The article of manufacture as defined in claim 30 , further causing the computer to operate so as to: calculate a score based upon an aspect ratio comparison of each identified grouping of substantially adjacent pixels in the representation and each identified grouping of substantially adjacent pixels in the second representation.

Claim 37

The article of manufacture as defined in claim 30 , further causing the computer to operate so as to: calculate a score based upon a texture comparison of each identified grouping of substantially adjacent pixels in the representation and each identified grouping of substantially adjacent pixels in the second representation.

Claim 38

The article of manufacture as defined in claim 30 , further causing the computer to operate so as to: calculate a score based upon a velocity comparison of each identified grouping of substantially adjacent pixels in the first representation and each identified grouping of substantially adjacent pixels in the second representation.

Claim 39

The article of manufacture as defined in claim 30 , further causing the computer to operate so as to: calculate a score based upon a color comparison of each identified grouping of substantially adjacent pixels in the first representation and each identified grouping of substantially adjacent pixels in the second representation.

Claim 40

The article of manufacture as defined in claim 36 , wherein the first representation represents differences between a third representation of a plurality of pixels and a fourth representation of a plurality of pixels, wherein second representation represents differences between a fifth representation of a plurality of pixels and the fourth representation of a plurality of pixels, further causing the computer to operate so as to: color sample pixel areas in the third and the fifth representations corresponding to pixel areas in each identified grouping of substantially adjacent pixels in the first and the second representations; average the color sampled pixel areas; and compare the averaged color sampled pixel areas.

Claim 41

The article of manufacture as defined in claim 37 , further causing the computer to operate so as to: color sample pixel areas in a predefined pattern in the third and the fifth representations.

Claim 42

The article of manufacture as defined in claim 37 , further causing the computer to operate so as to: combine a subset of the compared averaged color sampled pixel areas to provide a measure of color accuracy.

Claim 43

The article of manufacture as defined in claim 30 , further causing the computer to operate so as to: compare each score between each identified grouping of substantially adjacent pixels in the first representation and each identified grouping of substantially adjacent pixels in the second representation to a threshold value.

Claim 44

The article of manufacture as defined in claim 40 , further causing the computer to operate so as to: list each score between each identified grouping of substantially adjacent pixels in the first representation and each identified grouping of substantially adjacent pixels in the second representation according to a score value; match an identified grouping of substantially adjacent pixels in the first representation and an identified grouping of substantially adjacent pixels in the second representation according to highest score values; and remove the matched identified groupings from the listing.

Claim 45

The article of manufacture as defined in claim 41 , further causing the computer to operate so as to: track the matched identified groupings through the series of images.