Techniques for enabling or establishing the use of face recognition algorithms
First Claim
Patent Images
1. A method for performing recognition, method being implemented by one or more processors and comprising:
- determining a region of an image where an object is likely located, the object of the image including a plurality of features;
identifying multiple sets of hypotheses locations using a plurality of probabilistic models for each of the plurality of features of the object, wherein each set of hypotheses locations corresponds to a plurality of possible locations of one of the plurality of features of the object;
selecting a most likely hypothesis location for each of the multiple sets of hypotheses locations based on the probabilistic model that provides the highest likelihood for the plurality of features of the object;
calculating one or more pixel values at the most likely hypothesis location of each set of hypotheses locations; and
locating, using the one or more pixel values, one or more pixels of the image that correspond to each of the plurality of features of the object.
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Abstract
Embodiments described herein facilitate or enhance the implementation of image recognition processes which can perform recognition on images to identify objects and/or faces by class or by people.
121 Citations
18 Claims
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1. A method for performing recognition, method being implemented by one or more processors and comprising:
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determining a region of an image where an object is likely located, the object of the image including a plurality of features; identifying multiple sets of hypotheses locations using a plurality of probabilistic models for each of the plurality of features of the object, wherein each set of hypotheses locations corresponds to a plurality of possible locations of one of the plurality of features of the object; selecting a most likely hypothesis location for each of the multiple sets of hypotheses locations based on the probabilistic model that provides the highest likelihood for the plurality of features of the object; calculating one or more pixel values at the most likely hypothesis location of each set of hypotheses locations; and locating, using the one or more pixel values, one or more pixels of the image that correspond to each of the plurality of features of the object. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. A method for performing recognition, method being implemented by one or more processors and comprising:
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analyzing each image in a plurality of images, the plurality of images collectively depicting a plurality of different objects of an object class from various viewpoints or with various distortions, the plurality of images including a first image, depicting a first object of the object class with a first viewpoint or distortion, and a second image, depicting a second object of the object class with a second viewpoint or distortion that is different than the first viewpoint or distortion; wherein analyzing each image in the plurality of images includes, for each image in the plurality of images; determining a region of that image where an object of the object class is likely located, the object including a plurality of features, identifying multiple sets of hypotheses locations using a plurality of probabilistic models for each of the plurality of features of the object, wherein each set of hypotheses locations corresponds to a plurality of possible locations of one of the plurality of features of the object depicted in the image, selecting a most likely hypothesis location for each of the multiple sets of hypotheses locations based on the probabilistic model that provides the highest likelihood for the plurality of features of the object, calculating one or more pixel values at the most likely hypothesis location of each set of hypotheses locations, locating, using the one or more pixel values, one or more pixels of the image that correspond to each of the plurality of features of the object, and wherein the method further comprises enabling at least the first object and the second object to be compared based on pixels of the first image that correspond to each of the plurality of features of the first object, and pixels of the second image that correspond to each of the plurality of features of the second object. - View Dependent Claims (9, 10, 11, 12, 13, 14, 15, 16, 17)
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18. A computer system comprising:
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a memory that stores instructions; one or more processors, which access instructions from the memory to perform operations comprising; determine a region of an image where an object is likely located, the object of the image including a plurality of features; identify multiple sets of hypotheses locations using a plurality of probabilistic models for each of the plurality of features of the object, wherein each set of hypotheses locations corresponds to a plurality of possible locations of one of the plurality of features of the object; select a most likely hypothesis location for each of the multiple sets of hypotheses locations based on the probabilistic model that provides the highest likelihood for the plurality of features of the object; calculate one or more pixel values at the most likely hypothesis location of each set of hypotheses locations; and locate, using the one or more pixel values, one or more pixels of the image that correspond to each of the plurality of features of the object.
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Specification