Simultaneous extraction of functional face subspaces

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Facial variation divides into a number of functional subspaces. An improved method of measuring these was designed, within the space defined by an Appearance Model. Initial estimates of the subspaces (lighting, pose, identity, expression) were obtained by Principal Components Analysis on appropriate groups of faces. An iterative algorithm was applied to image codings to maximize the probability of coding across these non-orthogonal subspaces before obtaining the projection on each sub-space and recalculating the spaces. This procedure enhances identity recognition, reduces overall sub-space variance and produces Principal Components with greater span and less contamination.

Bibliographical metadata

Original languageEnglish
Title of host publicationProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition|Proc IEEE Comput Soc Conf Comput Vision Pattern Recognit
Place of PublicationLos Alamitos, CA, United States
PublisherIEEE
Pages492-497
Number of pages5
Volume1
Publication statusPublished - 1999
EventProceedings of the 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'99) - Fort Collins, CO, USA
Event duration: 1 Jul 1999 → …

Conference

ConferenceProceedings of the 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'99)
CityFort Collins, CO, USA
Period1/07/99 → …