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. © 2010 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Utsumi, Y., Iwai, Y., & Ishiguro, H. (2010). Face tracking and recognition considering the camera’s field of view. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6219 LNCS, pp. 52–63). https://doi.org/10.1007/978-3-642-14715-9_6
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