Face Recognition Based on Texture Discrimination by Using Geodesic Distance Approximations Between Multivariate Normal Distributions

Soldera, J and Dodson, CTJ and Scharcanski, J (2018) Face Recognition Based on Texture Discrimination by Using Geodesic Distance Approximations Between Multivariate Normal Distributions. IEEE Xplore.

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Abstract

Geodesic distances are a natural dissimilarity measure between probability distributions of a fixed type, and are used to discriminate texture in several image-based measurements. Besides, since there is no known closed-form solution for the geodesic distance between general multivariate normal distributions, we propose two efficient approximations to discriminate textures in the context of face recognition. Unlike the typical appearance-based approach that uses low-resolution grayscale face images, we propose a novel generative approach for face recognition based on texture discrimination. In the proposed approach, sparse facial features are extracted from high-resolution color face images using predefined landmark topologies, in which landmarks are in discriminative locations of face images. By adopting a common landmark topology, the dissimilarity between distinct face images can be scored in terms of the dissimilarities between the texture in their corresponding landmark vicinities. The proposed multivariate normal distributions represent the color intensities around each landmark location. The classification of new face samples occurs by determining the face image sample in the training set which minimizes the dissimilarity score. The proposed face recognition method was compared to methods representative of the state-of-the-art using color and grayscale face images, and presented higher recognition rates. Moreover, the proposed measures to discriminate textures tend to be efficient in face recognition and in general texture discrimination (e.g., texture recognition of material images), as our experiments suggest

Item Type:	Article
Uncontrolled Keywords:	Face, Image color analysis, Feature extraction, Face recognition, Topology, Gaussian distribution, Image resolution
Subjects:	MSC 2010, the AMS's Mathematics Subject Classification > 53 Differential geometry MSC 2010, the AMS's Mathematics Subject Classification > 60 Probability theory and stochastic processes
Depositing User:	Prof CTJ Dodson
Date Deposited:	13 May 2018 09:37
Last Modified:	13 May 2018 09:37
URI:	https://eprints.maths.manchester.ac.uk/id/eprint/2642

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