Face recognition with combined PCA-based datasets

A face recognition method operable on two or more collections of images, one or more of said images containing one or more facial regions, and using a processor to carry out the method, 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.

One or more processor readable media having program code embodied therein for programming one or more processors to perform a face recognition method for working with two or more collections of facial images, wherein the method comprises:

• (a) determining a first representation framework for a first collection of facial images including at least principle component analysis (PCA) features;
• (b) storing a representation of said first collection using said first representation framework;
• (c) determining a modified representation framework based on statistical properties of original facial image samples of a second collection of facial images and the stored representation of the first collection;
• (d) combining the stored representation of the first collection and the second collection without using original facial image samples including back-projecting the second collection into the first representation framework, combining the back-projected representation of the second collection and the stored representation of the first collection into a combined image collection (super-collection), and forward projecting the combined collection into the second representation framework;
• (e) storing a representation of the combined image collection (super-collection) using said modified representation framework;
• (f) comparing a representation of a current facial image, determined in terms of said modified representation framework, with one or more representations of facial images of the combined collection;
• and
• (g) based on the comparing, determining whether one or more of the facial images within the combined collection matches the current facial image.

One or more processor readable media having program code embodied therein for programming one or more processors 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.