Crowd Flow Segmentation based on Motion Vectors in H.264 Compressed Domain

Praveen, Gnana R and Babu, Venkatesh R (2014) Crowd Flow Segmentation based on Motion Vectors in H.264 Compressed Domain. In: IEEE International Conference on Electronics, Computing and Communication Technologies (IEEE CONECCT), JAN 06-07, 2014, Indian Inst Sci, Bangalore, INDIA.

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Abstract

In this work, we have explored the prospect of segmenting crowd flow in H. 264 compressed videos by merely using motion vectors. The motion vectors are extracted by partially decoding the corresponding video sequence in the H. 264 compressed domain. The region of interest ie., crowd flow region is extracted and the motion vectors that spans the region of interest is preprocessed and a collective representation of the motion vectors for the entire video is obtained. The obtained motion vectors for the corresponding video is then clustered by using EM algorithm. Finally, the clusters which converges to a single flow are merged together based on the bhattacharya distance measure between the histogram of the of the orientation of the motion vectors at the boundaries of the clusters. We had implemented our proposed approach on the complex crowd flow dataset provided by 1] and compared our results by using Jaccard measure. Since we are performing crowd flow segmentation in the compressed domain using only motion vectors, our proposed approach performs much faster compared to other pixel domain counterparts still retaining better accuracy.

Item Type:	Conference Proceedings
Series.:	IEEE International Conference on Electronics Computing and Communication Technologies
Publisher:	IEEE
Additional Information:	IEEE International Conference on Electronics, Computing and Communication Technologies (IEEE CONECCT), Indian Inst Sci, Bangalore, INDIA, JAN 06-07, 2014
Keywords:	Crowd Flow; Segmentation; Motion Vector Clustering; EM algorithm; H.264 compressed domain; k-means clustering
Department/Centre:	Division of Interdisciplinary Sciences > Supercomputer Education & Research Centre
Date Deposited:	01 Apr 2015 12:16
Last Modified:	01 Apr 2015 12:16
URI:	http://eprints.iisc.ac.in/id/eprint/51166

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