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Motion Attention Fusion Model Based Video Target Detection and Extraction |
LIU Long1,2, YUAN Xiang-Hui2 |
1.Faculty of Automation and Information Engineering, Xi'an University of Technology, Xi'an 710048 2.School of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an 710049 |
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Abstract Aiming at the limitation of target detection and extraction algorithms under global motion scene, a target detection algorithm based on motion attention fusion model is proposed according to the motion attention mechanism. Firstly, the preprocess, such as accumulation and median filtering, is applied on the motion vector field. Then, according to the temporal and spatial characteristics of the motion vector, the motion attention fusion model is defined to detect moving target. Finally, the edge of the video moving target is extracted accurately by the morphologic operation and the edge tracking algorithm. The experimental results of different global motion video sequences show the proposed algorithm has better veracity and speedup than other algorithms.
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Received: 09 May 2012
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