Robust face tracking using motion prediction in adaptive particle filters

Authors:
Sukwon Choi;Daijin Kim
Affiliations:
Dept. of Computer Science & Engineering, Pohang University of Science and Technology, Pohang, Korea;Dept. of Computer Science & Engineering, Pohang University of Science and Technology, Pohang, Korea
Venue:
ICIAR'07 Proceedings of the 4th international conference on Image Analysis and Recognition
Year:
2007

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Abstract

We propose an efficient real-time face tracking system that can follow fast movements. For face tracking, we use a particle filter that can handle arbitrary distributions. To track fast movements, we predict the motions using motion history and motion estimation, hence we can find the face with fewer particles. For observation model, we use active appearance model(AAM) to obtain an accurate face region, and update the model using incremental principle component analysis (IPCA). Occlusion handling scheme incorporates motion history to handle the moving face with occlusion. We present several experimental results to prove that our system shows better performance than previous works.