System and method for rapid face recognition
First Claim
1. A face recognition method using sparse representation and regularized least squares-based classification on a computing device, the method comprising:
- obtaining an image to be recognized as a test sample y and a set of training images of certain subjects as training sample matrix T;
obtaining a sparse representation of the test sample and the training samples including an initial estimation of a sparse vector a;
constructing a new face dictionary comprising training samples with non-zero corresponding coefficients in the sparse vector a for the initial estimation;
obtaining new coefficients by solving a regularized least squares problem based on the constructed new face dictionary; and
determining a face identity of the test sample based on minimum class residual calculated by using the new coefficients.
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Abstract
A face recognition method is provided to use sparse representation and regularized least squares-based classification on a computing device. The method includes obtaining an image to be recognized as a test sample y and a set of training images of certain subjects as training sample matrix T, obtaining a sparse representation of the test sample and the training samples including an initial estimation of a sparse vector a, and constructing a new face dictionary comprising training samples with non-zero corresponding coefficients in the sparse vector a for the initial estimation. The method also includes obtaining new coefficients by solving a regularized least squares problem based on the constructed new face dictionary, and determining a face identity of the test sample based on minimum class residual calculated by using the new coefficients.
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Citations
20 Claims
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1. A face recognition method using sparse representation and regularized least squares-based classification on a computing device, the method comprising:
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obtaining an image to be recognized as a test sample y and a set of training images of certain subjects as training sample matrix T; obtaining a sparse representation of the test sample and the training samples including an initial estimation of a sparse vector a; constructing a new face dictionary comprising training samples with non-zero corresponding coefficients in the sparse vector a for the initial estimation; obtaining new coefficients by solving a regularized least squares problem based on the constructed new face dictionary; and determining a face identity of the test sample based on minimum class residual calculated by using the new coefficients. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A non-transitory computer-readable medium having computer program for, when being executed by a processor, performing a face recognition method using sparse representation and regularized least squares-based classification on a computing device, the method comprising:
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obtaining an image to be recognized as a test sample y and a set of training images of certain subjects as training sample matrix T; obtaining a sparse representation of the test sample and the training samples including an initial estimation of a sparse vector a; constructing a new face dictionary comprising training samples with non-zero corresponding coefficients in the sparse vector a for the initial estimation; obtaining new coefficients by solving a regularized least squares problem based on the constructed new face dictionary; and determining a face identity of the test sample based on minimum class residual calculated by using the new coefficients. - View Dependent Claims (12, 13, 14, 15, 16, 17, 18, 19, 20)
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Specification