Method and apparatus for unsupervised learning of discriminative edge measures for vehicle matching between non-overlapping cameras
First Claim
1. A method for unsupervised learning of measures for matching objects between images from at least two non-overlapping cameras, comprising:
- collecting at least two pairs of feature maps, wherein the at least two pairs of feature maps are derived from features of objects captured in the images;
computing, as a function of at least two pairs of feature maps, at least first and second match measures, wherein the first match measure is of a same class and the second match measure is of a different class, , and wherein objects in the same class are deemed to match.
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Abstract
A method and apparatus for unsupervised learning of measures for matching objects between images from at least two non-overlapping cameras is disclosed The method includes collecting at least one two pairs of feature maps, where the at least one two pairs of feature maps are derived from features of objects captured in the images. The method further includes computing, as a function of at least one two pairs of feature maps, at least one first and second match measures, wherein the first match measure is of a same class and the second match measure is of a different class.
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Citations
20 Claims
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1. A method for unsupervised learning of measures for matching objects between images from at least two non-overlapping cameras, comprising:
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collecting at least two pairs of feature maps, wherein the at least two pairs of feature maps are derived from features of objects captured in the images;
computing, as a function of at least two pairs of feature maps, at least first and second match measures, wherein the first match measure is of a same class and the second match measure is of a different class, , and wherein objects in the same class are deemed to match. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. An apparatus for matching objects between images from at least two non-overlapping cameras, comprising:
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means for collecting at least one pair of feature maps, wherein the at least one pair of feature maps are derived from features of objects captured in the images;
means for computing, as a function of at least two pairs of feature maps, at least first and second match measures, wherein the first match measure is of a same class and the second match measure is of a different class, and wherein objects in the same class are deemed to match - View Dependent Claims (11, 12, 13, 14, 15, 16)
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17. A method for unsupervised learning of measures for matching objects between images from at least two non-overlapping cameras, comprising:
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collecting at least two pairs of feature maps, wherein the at least two pairs of feature maps are derived from features of objects captured in the images;
learning from the at least two pairs of feature maps respective outlier and inlier distributions;
computing, as a function of at least two pairs of feature maps and the respective outlier and inlier distributions, at least first and second match measures, wherein the first match measure is of a same class and the second match measure is of a different class, and wherein objects in the same class are deemed to match - View Dependent Claims (18, 19, 20)
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Specification