Face recognition with combined PCA-based datasets
First Claim
1. A consumer digital camera including a processor programmed by digital code to perform a face recognition method for working with two or more collections of facial images, wherein the method comprises:
- (a) determining distinct representation frameworks for first and second sets of facial regions extracted from corresponding image collections each framework including at least principle component analysis (PCA) features;
(b) storing representations of said first and second sets of facial regions using their respective representation frameworks;
(c) determining a third, distinct representation framework based on the representations of the first and second sets of facial regions;
(d) combining the stored representation of the first and the second sets of facial regions without using original facial image samples;
including back-projecting the sets of facial regions into their respective representation frameworks, combining the two back-projected representations of these sets of facial regions into a combined dataset, and forward projecting the combined dataset into the third representation framework;
(e) storing a representation of the combined dataset using said third representation framework;
(f) comparing a representation of a current facial region, determined in terms of said third representation framework, with one or more representations of facial images of the combined dataset; and
(g) based on the comparing, determining whether one or more of the facial images within the combined dataset matches the current facial image.
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Abstract
A representation framework is determined in a face recognition method for a first collection of facial images including at least principle component analysis (PCA) features. A representation of said first collection is stored using the representation framework. A modified representation framework is determined based on statistical properties of original facial image samples of a second collection of facial images and the stored representation of the first collection. The first and second collections are combined without using original facial image samples. A representation of the combined image collection (super-collection) is stored using the modified representation framework.
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Citations
7 Claims
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1. A consumer digital camera including a processor programmed by digital code to perform a face recognition method for working with two or more collections of facial images, wherein the method comprises:
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(a) determining distinct representation frameworks for first and second sets of facial regions extracted from corresponding image collections each framework including at least principle component analysis (PCA) features; (b) storing representations of said first and second sets of facial regions using their respective representation frameworks; (c) determining a third, distinct representation framework based on the representations of the first and second sets of facial regions; (d) combining the stored representation of the first and the second sets of facial regions without using original facial image samples;
including back-projecting the sets of facial regions into their respective representation frameworks, combining the two back-projected representations of these sets of facial regions into a combined dataset, and forward projecting the combined dataset into the third representation framework;(e) storing a representation of the combined dataset using said third representation framework; (f) comparing a representation of a current facial region, determined in terms of said third representation framework, with one or more representations of facial images of the combined dataset; and (g) based on the comparing, determining whether one or more of the facial images within the combined dataset matches the current facial image. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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Specification