METHOD AND APPARATUS FOR MATCHING LOCAL SELF-SIMILARITIES
First Claim
1. A method comprising:
- matching at least portions of first and second signals using local self-similarity descriptors of said signals,wherein said matching comprises;
computing a local self-similarity descriptor for each one of at least a portion of points in said first signal;
forming a query ensemble of said descriptors for said first signal; and
seeking an ensemble of descriptors of said second signal which matches said query ensemble of descriptors.
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Abstract
A method includes matching at least portions of first, second signals using local self-similarity descriptors of the signals. The matching includes computing a local self-similarity descriptor for each one of at least a portion of points in the first signal, forming a query ensemble of the descriptors for the first signal and seeking an ensemble of descriptors of the second signal which matches the query ensemble of descriptors. This matching can be used for image categorization, object classification, object recognition, image segmentation, image alignment, video categorization, action recognition, action classification, video segmentation, video alignment, signal alignment, multi-sensor signal alignment, multi-sensor signal matching, optical character recognition, image and video synthesis, correspondence estimation, signal registration and change detection. It may also be used to synthesize a new signal with elements similar to those of a guiding signal synthesized from portions of the reference signal. Apparatus is also included.
92 Citations
67 Claims
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1. A method comprising:
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matching at least portions of first and second signals using local self-similarity descriptors of said signals, wherein said matching comprises; computing a local self-similarity descriptor for each one of at least a portion of points in said first signal; forming a query ensemble of said descriptors for said first signal; and seeking an ensemble of descriptors of said second signal which matches said query ensemble of descriptors. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34)
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35. An apparatus comprising:
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a similarity detector to match at least portions of first and second signals using local self-similarity descriptors of said signals wherein said similarity detector comprises; a descriptor calculator to compute a local self-similarity descriptor for each one of at least a portion of points in said first signal; and a descriptor ensemble matcher to form a query ensemble of said descriptors for said first signal and to seek an ensemble of descriptors of said second signal which matches said query ensemble of descriptors. - View Dependent Claims (36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65)
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66. A method for generating a local self-similarity descriptor, the method comprising:
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calculating a patch-region similarity function between a patch of a signal to a region within a signal; and transforming said patch-region similarity function into a binned representation, wherein the bins of said binned representation are radially increasing in size.
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67. An apparatus for generating a local self-similarity descriptor, the apparatus comprising:
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a similarity generator to calculate a patch-region similarity function between a patch of a signal to a region within a signal; and a descriptor generator to transform said patch-region similarity function into a binned representation, wherein the bins of said binned representation are radially increasing in size.
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Specification