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In this paper, we propose a macro-observation scheme for unusual event detection in daily life, where motions in time-space domain are described by a global representation and individual activities do not have to be defined and modeled beforehand. The proposed representation records the time-space energy of motions of all moving objects in a scene without segmenting individual object parts or tracking...
Based on the observation that motion of different pixels from the same target has very similar spatial-temporal properties in bus video surveillance images, a feature point's trajectory clustering method is proposed to estimate passenger flow in this paper. Firstly, the pyramid-based optical flow algorithm is utilized to tracking the feature point's movement in the images; then, their trajectories...
Detecting dominant motion flows in crowd scenes is one of the major problems in video surveillance. This is particularly difficult in unstructured crowd scenes, where the participants move randomly in various directions. This paper presents a novel method which utilizes SIFT features' flow vectors to calculate the dominant motion flows in both unstructured and structured crowd scenes. SIFT features...
Detecting and segmenting moving objects in dynamic scenes is a hard but essential task in a number of applications such as surveillance. Most existing methods only give good results in the case of persistent or slowly changing background, or if both the objects and the background are rigid. In this paper, we propose a new method for direct detection and segmentation of foreground moving objects in...
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