Moving object detection is a challenging issue in computer vision. In this paper, a new detection method via superpixels is proposed based on spatiotemporal multi-cues fusion. First, the current frame is segmented into a set of superpixels using simple linear iterative clustering and the subblocks of foreground superpixels containing motion information are captured according to the time-varying cue of inter-frame pixel-level. Then, a target model of the previous frame, which is established on the basis of the consistency principle of motion target and space clues of a target, are combined to further determine the detection window including the moving object. Finally, the problem of object detection is converted to object segmentation and an object is divided from the detection window utilizing the dense corner detection. Experimental results using several challenging public video sequences show the effectiveness and superiority of the proposed method compared with other state-of-the-art detection approaches.
宋涛,李鸥,刘广怡. 基于空时多线索融合的超像素运动目标检测方法[J]. 电子与信息学报, 2016, 38(6): 1503-1511.
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