Video tracking using block matching

被引:0
|
作者
Hariharakrishnan, K [1 ]
Schonfeld, D [1 ]
Raffy, P [1 ]
Yassa, F [1 ]
机构
[1] Multimedia Commun Lab, UIC, Chicago, IL 60607 USA
关键词
object tracking; video compression; content retrieval; motion estimation; occlusion detection; K-means clustering;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
A tracking algorithm that predicts the object contour using motion vector information is proposed in this paper. Tracking is achieved by predicting the object boundary using motion vectors, followed by contour update, using occlusions/disocclusion detection. An adaptive block-based approach has been used for estimating motion between frames. An efficient modulation scheme is used to control the gap between frames used for object tracking. The algorithm for detecting occlusion proceeds in two steps. First, covered regions are estimated from the displaced frame difference. These covered regions are classified into actual occlusions and false alarms using motion characteristics. Disocclusion detection is also performed in a similar manner. The immediate applications of the proposed tracking algorithm are video compression using MPEG-4 and content retrieval based on standards like H.26L. Preliminary simulation results demonstrate the performance of the proposed algorithm.
引用
收藏
页码:945 / 948
页数:4
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