Fast multi-view face tracking with pose estimation

In this paper, a fast and effective multi-view face tracking algorithm with head pose estimation is introduced. For modeling the face pose, we employ a tree of boosted classifiers built using either Haar-like filters or Gauss filters. A first classifier extracts faces of any pose from the background. Then, more specific classifiers discriminate between different poses. The tree of classifiers is trained by hierarchically sub-sampling the pose space. Finally, Condensation algorithm is used for tracking the faces. Experiments show large improvements in terms of detecting rate and processing speed compared to state-of-the-art algorithms.

Presented at:
16th European Signal Processing Conference, Lausanne, Switzerland, August 25-29

 Record created 2011-02-07, last modified 2018-03-17

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