System and method for adaptive face recognition
First Claim
1. A non-transitory electronic-processor-readable medium having a plurality of electronic processor executable instructions stored thereon that, when executed by an electronic processor, causes the electronic processor to perform a method of facial recognition, the method comprising:
- inputting at least one test image, j, into at least one electronic processor;
performing adaptive high-pass filtering, HF, on said at least one test image, j, to increase the number of keypoints, KP, in said at least one test image, j, to reduce changes in illumination in said at least one test image, j, wherein said keypoints, KP, are structures of interest in said at least one test image, j, including eyes, brows, nose, mouth, and hairline features, wherein said adaptive high-pass filtering, HF, uses at least two high-pass filters having different spatial frequency bandwidths dependent on the pixel size of said at least one test image, j;
computing at least one scale invariant feature transform (SIFT) descriptor, N, for each of said at least one test image, j;
recognizing said new subject of interest in said at least one test image, j, by using an optimization technique, l1, to search for a best match of said new subject of interest in said at least one test image, j, in said at least one database having a plurality of pixilated face images of known subjects of interest;
determining whether to learn and alter the current knowledge of said dictionary, A from Ac(j-1) to Ac(j);
outputting a class having maximum output, qmax;
when it is determined to learn, adapt said dictionary, A, using reversed—
orthogonal matching pursuit (OMP); and
iterating through said recognizing said new subject of interest in said at least one test image, j, by using an optimization technique, l1, to search for a best match of said new subject of interest in said at least one test image, j, in said at least one database having a plurality of pixilated face images of known subjects of interest task, said determining whether to learn and alter the current knowledge of said dictionary, A task, and said outputting a class having maximum output, qmax, until it is determined not to learn.
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Abstract
A system and method for adaptive face recognition includes at least one electronic processor having a central processing unit. At least one database having a plurality of pixilated face images of known subjects of interest is associated with the processor. At least one test image of a new subject of interest is configured for input into the electronic processor. A classification processing tool is associated with the electronic processor. The classification processing tool is configured to build a dictionary and provide a classification match of the test image with one of the plurality of pixilated face images of known subjects of interest. At least one device is associated with the processor and configured to output the classification match in a tangible medium.
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Citations
4 Claims
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1. A non-transitory electronic-processor-readable medium having a plurality of electronic processor executable instructions stored thereon that, when executed by an electronic processor, causes the electronic processor to perform a method of facial recognition, the method comprising:
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inputting at least one test image, j, into at least one electronic processor; performing adaptive high-pass filtering, HF, on said at least one test image, j, to increase the number of keypoints, KP, in said at least one test image, j, to reduce changes in illumination in said at least one test image, j, wherein said keypoints, KP, are structures of interest in said at least one test image, j, including eyes, brows, nose, mouth, and hairline features, wherein said adaptive high-pass filtering, HF, uses at least two high-pass filters having different spatial frequency bandwidths dependent on the pixel size of said at least one test image, j; computing at least one scale invariant feature transform (SIFT) descriptor, N, for each of said at least one test image, j; recognizing said new subject of interest in said at least one test image, j, by using an optimization technique, l1, to search for a best match of said new subject of interest in said at least one test image, j, in said at least one database having a plurality of pixilated face images of known subjects of interest; determining whether to learn and alter the current knowledge of said dictionary, A from Ac(j-1) to Ac(j); outputting a class having maximum output, qmax; when it is determined to learn, adapt said dictionary, A, using reversed—
orthogonal matching pursuit (OMP); anditerating through said recognizing said new subject of interest in said at least one test image, j, by using an optimization technique, l1, to search for a best match of said new subject of interest in said at least one test image, j, in said at least one database having a plurality of pixilated face images of known subjects of interest task, said determining whether to learn and alter the current knowledge of said dictionary, A task, and said outputting a class having maximum output, qmax, until it is determined not to learn. - View Dependent Claims (2, 3, 4)
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Specification