Abstract
We propose a method that tracks and recognizes faces simultaneously. In previous methods, features needed to be extracted twice for tracking and recognizing faces in image sequences because the features used for face recognition are different from those used for face tracking. To reduce the computational cost, we propose a probabilistic model for face tracking and recognition and a system that performs face tracking and recognition simultaneously using the same features. The probabilistic model handles any overlap in the camera’s field of view, something that is ignored in previous methods. The model thus deals with face tracking and recognition using multiple overlapping image sequences. Experimental results show that the proposed method can track and recognize multiple faces simultaneously.
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Utsumi, Y., Iwai, Y., Ishiguro, H. (2010). Face Tracking and Recognition Considering the Camera’s Field of View. In: Salah, A.A., Gevers, T., Sebe, N., Vinciarelli, A. (eds) Human Behavior Understanding. HBU 2010. Lecture Notes in Computer Science, vol 6219. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14715-9_6
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DOI: https://doi.org/10.1007/978-3-642-14715-9_6
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