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Extending Non-negative Matrix Factorisation to 3D Registered Data

Koppen, WP, Christmas, WJ, Crouch, DJM, Bodmer, WF and Kittler, JV (2016) Extending Non-negative Matrix Factorisation to 3D Registered Data In: ICB-2016: The 9th IAPR International Conference on Biometrics, 2016-06-13 - 2016-06-16, Halmstad, Sweden.

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Abstract

The use of non-negative matrix factorisation (NMF) on 2D face images has been shown to result in sparse feature vectors that encode for local patches on the face, and thus provides a statistically justified approach to learning parts from wholes. However successful on 2D images, the method has so far not been extended to 3D images. The main reason for this is that 3D space is a continuum and so it is not apparent how to represent 3D coordinates in a non-negative fashion. This work compares different non-negative representations for spatial coordinates, and demonstrates that not all non-negative representations are suitable. We analyse the representational properties that make NMF a successful method to learn sparse 3D facial features. Using our proposed representation, the factorisation results in sparse and interpretable facial features.

Item Type: Conference or Workshop Item (Conference Paper)
Subjects : Electronic Engineering
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :
NameEmailORCID
Koppen, WPUNSPECIFIEDUNSPECIFIED
Christmas, WJUNSPECIFIEDUNSPECIFIED
Crouch, DJMUNSPECIFIEDUNSPECIFIED
Bodmer, WFUNSPECIFIEDUNSPECIFIED
Kittler, JVUNSPECIFIEDUNSPECIFIED
Date : 13 June 2016
Identification Number : 10.1109/ICB.2016.7550083
Copyright Disclaimer : © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works
Related URLs :
Depositing User : Symplectic Elements
Date Deposited : 26 Oct 2016 08:24
Last Modified : 31 Oct 2017 18:51
URI: http://epubs.surrey.ac.uk/id/eprint/812612

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