We evaluate a new approach to face recognition using a variety of surface representations of three-dimensional facial structure. Applying principal component analysis (PCA), we show that high levels of recognition accuracy can be achieved on a large database of 3D face models, captured under conditions that present typical difficulties to more conventional two-dimensional approaches. Applying a ran-c of image processing, techniques we identify the most effective surface representation for use in such application areas as security surveillance, data compression and archive searching.
|Copyright, Publisher and Additional Information:||© 2004 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.|
|Institution:||The University of York|
|Academic Units:||The University of York > Computer Science (York)|
|Depositing User:||Repository Assistant|
|Date Deposited:||25 Aug 2006|
|Last Modified:||06 Feb 2017 15:23|