Head Pose Estimation in Seminar Room Using Multi View Face Detectors
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.
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- 1.Gong, S., Mckenna, S., Collins, J.: An investigation into face pose distributions. In: FG (1996)Google Scholar
- 2.Li, S., Peng, X., Hou, X., Zhang, H., Cheng, Q.: Multi-view face pose estimation based on supervised ISA learning. In: FG (2002)Google Scholar
- 3.Li, S., Zhang, Z.: FloatBoost learning and statistical face detection. IEEE Trans. Pattern Anal. Machine Intell. 26(9) (2004)Google Scholar
- 4.Schneiderman, H., Kanade, T.: A statistical method for 3D object detection applied to faces and cars. In: Proc. Conf. Computer Vision Pattern Recog. (2000)Google Scholar
- 7.Viola, P., Jones, M.: Robust real time object detection. In: Proc. IEEE ICCV Work. Statistical and Computational Theories of Vision (2001)Google Scholar
- 9.CHIL: Computers in the Human Interaction Loop. Project web-site: http://chil.server.de