Active appearance models fitting with occlusion

Authors:
Xin Yu;Jinwen Tian;Jian Liu
Affiliations:
Huazhong University of Science and Technology, State Key Laboratory for Multi-spectral Information Processing Technologies, Wuhan, P.R. China;Huazhong University of Science and Technology, State Key Laboratory for Multi-spectral Information Processing Technologies, Wuhan, P.R. China;Huazhong University of Science and Technology, State Key Laboratory for Multi-spectral Information Processing Technologies, Wuhan, P.R. China
Venue:
EMMCVPR'07 Proceedings of the 6th international conference on Energy minimization methods in computer vision and pattern recognition
Year:
2007

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Abstract

In this paper, we propose an Active Appearance Models (AAMs) fitting algorithm, adaptive fitting algorithm, to localize an object in an image containing occlusion. The adaptive fitting algorithm conducts the fitting problem of AAMs containing object occlusion in a statistical framework. We assume that the residual errors can be treated as mixture statistical model of Gaussian and uniform model. We then reformulated the basic fitting algorithm and maximum a-posteriori (MAP) estimation algorithm of model parameter for AAMs to make the adaptive fitting algorithm. Extensive experiments are provided to demonstrate our algorithm.