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Flow analysis of crowd and traffic videos is an important video surveillance task. In this work, we propose an algorithm for long-term flow segmentation and dominant flow extraction in traffic videos. Each flow segment is a temporal sequence of image segments indicating the motion of a vehicle in the camera view. This flow segmentation is done in the framework of Conditional Random Fields using motion...
In this paper, we have proposed a simple yet robust novel approach for segmentation of high density crowd flows based on super-pixels in H.264 compressed videos. The collective representation of the motion vectors of the compressed video sequence is transformed to color map and super-pixel segmentation is performed at various scales for clustering the coherent motion vectors. The number of dynamically...
This paper discusses a novel fast approach for moving object detection in H.264/AVC compressed domain for video surveillance applications. The proposed algorithm initially segments out edges from regions with motion at macroblock level by utilizing the gradient of quantization parameter over 2D-image space. A spatial median filtering of the segmented edges followed by weighted temporal accumulation...
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