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Reliable object tracking in complex visual environment is a challenging problem in the field of computer vision. One of the common problems in object tracking is partial and full object occlusions. And especially in the condition of long- lived full occlusion during which the full occlusion lasts for tens of frames, the tracking is more difficult. This paper proposes an occlusion handling scheme based...
SIFT is one of the most robust feature extraction algorithms and widely used in object tracking field. While invariant to scale, rotation and other image transforms, the traditional SIFT algorithm is rather time-consuming in creating description of the large number of keypoints. Aiming at reducing tracking time and complexity to achieve real time compliance, this paper proposes Homography Matrix based...
The Continuously Adaptive Mean Shift algorithm (CAMShift) is an adaptation of mean shift algorithm for object tracking especially for head and face tracking. Traditional CAMShift can not deal with multi-colored object tracking and situations when similar colors exist nearby. In this paper, a new approach towards these problems using CAMShift with weighted back projection is proposed. In our approach,...
A large number of surveillance applications requires narrow channel transmission and limited capacity storage, since very low bit-rate techniques becomes necessary. For many surveillance applications, motive objects contain most interest information. This paper proposed an enhanced motion block detector, which includes a pre-stage for adaptively classifying macroblocks into motive and static blocks...
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