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The tracking of facial activities from video is an important and challenging problem. Nowadays, many computer vision techniques have been proposed to characterize the facial activities in the following three levels (from local to global): First, in the bottom level, the facial feature tracking focuses on detecting and tracking the prominent local landmarks surrounding facial components (e.g. mouth,...
Video-based tracking of contours on the human body has been shown to be useful for many applications, including gait and gesture recognition, posture estimation, and activity analysis. We present a contour tracking method that incorporates a novel edge feature and fuzzy contour template. We apply our method in tracking the motions of older adults exercising in a gym environment. The output of our...
We propose a person-dependent, manifold-based approach for modeling and tracking rigid and nonrigid 3D facial deformations from a monocular video sequence. The rigid and nonrigid motions are analyzed simultaneously in 3D, by automatically fitting and tracking a set of landmarks. We do not represent all nonrigid facial deformations as a simple complex manifold, but instead decompose them on a basis...
In this paper, we propose a novel object tracking algorithm in video sequences. The formulation of the object tracking is based on variational calculus, where an adaptive parametric mixture model is used for object features representation. The tracking is based on matching the object mixture models between successive frames of the sequence by using active contours while adapting the mixture model...
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