Improvement of a person labelling method using extracted knowledge on costume
CAIP'05 Proceedings of the 11th international conference on Computer Analysis of Images and Patterns
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Robust real-time face tracking is a challenging task. This paper presents an algorithm for tracking faces of multiple people even in case of total occlusion. The method uses the color distribution of each face with the mean shift tracking method. Mean shift tracking is fast and robust to partial occlusion, and it is rotation invariant and computationally efficient. Since the mean shift algorithm does not deal with the problem of total occlusion, we overcome this problem by using an occlusion grid to detect occlusion. We then use the color distribution of the occluded person's clothes to distinguish that person after the occlusion ends. We also use the speed and the trajectory of the occluded person to predict the locations that should be searched after occlusion ends. The proposed face tracking method integrates multiple features to handle tracking of multiple people even in case of occlusion. The experiments show the robustness of the algorithm.