ROBUST FEATURE IDENTIFICATION FOR IMAGE-BASED OBJECT RECOGNITION
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Abstract
Techniques are provided that include identifying robust features within a training image. Training features are generated by applying a feature detection algorithm to the training image, each training feature having a training feature location within the training image. At least a portion of the training image is transformed into a transformed image in accordance with a predefined image transformation. Transform features are generated by applying the feature detection algorithm to the transformed image, each transform feature having a transform feature location within the transformed image. The training feature locations of the training features are mapped to corresponding training feature transformed locations within the transformed image in accordance with the predefined image transformation, and a robust feature set is compiled by selecting robust features, wherein each robust feature represents a training feature having a training feature transformed location proximal to a transform feature location of one of the transform features.
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Citations
60 Claims
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1-31. -31. (canceled)
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32. A product image feature detection device comprising:
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a tangible, non-transitory, computer-readable memory configured to store robust feature detection software instructions including at least one implementation of a feature detection algorithm, and at least one product training image; and at least one processor coupled with the memory that, upon execution of the robust feature detection software instructions; generates training features from the at least one product training image according to the at least one implementation of the feature detection algorithm, wherein each training feature has a corresponding training feature location within the at least one product training image; transforms at least a portion of the at least one product training image according to an image transformation, thereby forming a transformed image portion; generates transform features from the transformed image portion according to the at least one implementation of the feature detection algorithm, wherein each transform feature has a corresponding transform feature location within the transformed image portion; and stores in the memory a set of robust features, wherein each robust feature in the set represents a training feature, based on the image transform, having a training feature transformed location proximal to a transform feature location. - View Dependent Claims (33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58)
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59. A product image feature detection method comprising:
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generating training features from at least one product training image according to at least one implementation of a feature detection algorithm, wherein each training feature has a corresponding training feature location within the at least one product training image; transforming at least a portion of the at least one product training image according to an image transformation, thereby forming a transformed image portion; generating transform features from the transformed image portion according to the at least one implementation of the feature detection algorithm, wherein each transform feature has a corresponding transform feature location within the transformed image portion; and storing in memory a set of robust features, wherein each robust feature in the set represents a training feature, based on the image transform, having a training feature transformed location proximal to a transform feature location.
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60. A computer program product embedded in a non-transitory computer readable medium comprising product image feature detection instructions executable by a computer processor to perform operations comprising:
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generating training features from at least one product training image according to at least one implementation of a feature detection algorithm, wherein each training feature has a corresponding training feature location within the at least one product training image; transforming at least a portion of the at least one product training image according to an image transformation, thereby forming a transformed image portion; generating transform features from the transformed image portion according to the at least one implementation of the feature detection algorithm, wherein each transform feature has a corresponding transform feature location within the transformed image portion; and storing in memory a set of robust features, wherein each robust feature in the set represents a training feature, based on the image transform, having a training feature transformed location proximal to a transform feature location.
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Specification