H.264 COMPRESSED VIDEO CLASSIFICATION USING HISTOGRAM OF ORIENTED MOTION VECTORS (HOMV)

Biswas, Sovan and Babu, Venkatesh R (2013) H.264 COMPRESSED VIDEO CLASSIFICATION USING HISTOGRAM OF ORIENTED MOTION VECTORS (HOMV). In: IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), MAY 26-31, 2013, Vancouver, CANADA, pp. 2040-2044.

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Abstract

In this paper, we have proposed a simple and effective approach to classify H.264 compressed videos, by capturing orientation information from the motion vectors. Our major contribution involves computing Histogram of Oriented Motion Vectors (HOMV) for overlapping hierarchical Space-Time cubes. The Space-Time cubes selected are partially overlapped. HOMV is found to be very effective to define the motion characteristics of these cubes. We then use Bag of Features (B OF) approach to define the video as histogram of HOMV keywords, obtained using k-means clustering. The video feature, thus computed, is found to be very effective in classifying videos. We demonstrate our results with experiments on two large publicly available video database.

Item Type:	Conference Proceedings
Series.:	International Conference on Acoustics Speech and Signal Processing ICASSP
Publisher:	IEEE
Additional Information:	Copyright for this article belongs to the IEEE,USA
Keywords:	Video Classification; Compressed Domain; H.264; Histogram of Oriented Motion Vectors; Bag of Features
Department/Centre:	Division of Interdisciplinary Sciences > Supercomputer Education & Research Centre
Date Deposited:	26 Feb 2014 07:49
Last Modified:	26 Feb 2014 07:55
URI:	http://eprints.iisc.ac.in/id/eprint/48484

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