Real-time moving target Detection in the dynamic background

Moving target detection in the dynamic background, such as optical flow detect, is an expensive method, which is hard to satisfy its real time requirement in the project. In this paper, a new method is proposed, which synthesizes Lucas-Kanade, Hierarchical clustering and secondary clustering algorithms together that can rapidly detect moving targets. Since Hierarchical clustering is a high time exhausting algorithm, in order to reduce the time consuming, parts of the clustering algorithm are replaced by interframe calculation and secondary clustering. The experiments show that this method is accurate and real-time in detecting the moving target in the moving background.

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