Mixture of Classifiers for Face Recognition across Pose

Document Type

Article

Publication Date

12-1-2012

Abstract

A two dimensional Mixture of Classifiers (MoC) method is presented in this chapter for face recognition across pose. The 2D MoC method performs first pose classification with predefined pose categories and then face recognition within each individual pose class. The main contributions of the paper come from (i) proposing an effective pose classification method by addressing the scales problem of images in different pose classes, and (ii) applying pose-specific classifiers for face recognition. Comparing with the 3D methods for face recognition across pose, the 2D MoC method does not require a large number of manual annotations or a complex and expensive procedure of 3D modeling and fitting. Experimental results using a data set from the CMU PIE database show the feasibility of the 2D MoC method. © Springer-Verlag Berlin Heidelberg 2012.

Identifier

84885604129 (Scopus)

ISBN

[9783642284564]

Publication Title

Intelligent Systems Reference Library

External Full Text Location

https://doi.org/10.1007/978-3-642-28457-1_5

e-ISSN

18684408

ISSN

18684394

First Page

73

Last Page

92

Volume

37

This document is currently not available here.

Share

COinS