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Robust tracking is a challenging problem, due to intrinsic appearance variability of objects caused by in-plane or out-plane rotation and extrinsic factors change such as illumination, occlusion, background clutter and local blur. In this paper, we present a novel framework which uses an on-line AdaBoost algorithm as PSO's fitness function to search object and attain the efficiency and robustness...
In this paper, we proposed an enhanced kernel based algorithm for visual tracking based on the video sequences captured from a fixed camera on the top of the scene. The technique presented here employs the image color intensity information and the local binary pattern (LBP) to construct a four dimensional histogram representative of the color intensity values and the texture of the target under study...
In this paper, an effective face tracking algorithm based on the combination of shape and texture information is proposed. The edge map is used to represent the shape of a face, while the texture information is characterized by the local binary pattern (LBP). As the face patterns to be tracked in consecutive frames are highly correlated, an accurate tracking can be achieved by searching for the shortest...
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