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In this paper, a multiple features face tracking algorithm based on particle filter is proposed. Particle filter can effectively combine multiple face features information which supply robustness in different environments. Meanwhile, our approach makes use of the invariance to rotation and translation of color histogram central moment and statistical characteristic of multiple resolution Sobel Local...
This paper presents a face-tracking algorithm based on particle filter framework. Firstly, a target state is obtained using conventional color histograms. Secondly, a tracking method is proposed on the basis of seven moment invariants, and another state vector is also computed using this approach. Furthermore, the weights of the two state vectors are computed according to Euclidean distance between...
In this paper, a multiple features face tracking algorithm based on the particle filter is proposed. Since the particle filter can effectively combine multiple face features information which represents different characteristics, and supply robustness in different environments, we combine the robustness and invariance to rotation and translation of color histogram central moment and the accuracy and...
A new algorithm for face tracking is proposed. Color information provides an effective cue for face tracking due to its robustness to scaling, rotation and translation. But the main limitation of color cue is that it can be easily interrupted by the camouflage objects that have the same or similar color with the target face. In order to achieve robust face tracking performance, the texture feature...
This paper addresses the problem of object tracking in diving video sequences by particle filter. Because the diversity of motions in diving video sequences such as bouncing on the springboard, somersaulting in the air increases the difficulty to construct particle motion model, this paper presents an object tracking method in diving video sequences by particle filter with multiple motion models....
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