Statistical framework for facial pose classification

Authors:
Ajay Jaiswal;Nitin Kumar;R. K. Agrawal
Affiliations:
School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi, India;School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi, India;School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi, India
Venue:
MICAI'12 Proceedings of the 11th Mexican international conference on Advances in Artificial Intelligence - Volume Part I
Year:
2012

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Abstract

Pose classification is one of the important steps in some pose invariant face recognition methods. In this paper, we propose to use: (i) Partial least square (PLS) and (ii) Linear regression for facial pose classification. The performance of these two approaches is compared with two edge based approaches and pose-eigenspace approach in terms of classification accuracy. Experimental results on two publicly available face databases (PIE and FERET) show that the regression based approach outperforms other approaches for both the databases.