Head pose estimation in seminar room using multi view face detectors

Authors:
Zhenqiu Zhang;Yuxiao Hu;Ming Liu;Thomas Huang
Affiliations:
Beckman Institute, University of Illinois, Urbana, IL;Beckman Institute, University of Illinois, Urbana, IL;Beckman Institute, University of Illinois, Urbana, IL;Beckman Institute, University of Illinois, Urbana, IL
Venue:
CLEAR'06 Proceedings of the 1st international evaluation conference on Classification of events, activities and relationships
Year:
2006

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Abstract

Head pose estimation in low resolution is a challenge problem. Traditional pose estimation algorithms, which assume faces have been well aligned before pose estimation, would face much difficulty in this situation, since face alignment itself does not work well in this low resolution scenario. In this paper, we propose to estimate head pose using view-based multi-view face detectors directly. Naive Bayesian classifier is then applied to fuse the information of head pose from multiple camera views. To model the temporal changing of head pose, Hidden Markov Model is used to obtain the optimal sequence of head pose with greatest likelihood.