Compressed Domain Human Motion Recognition using Motion History Information

Babu, Venkatesh R and Ramakrishnan, KR (2003) Compressed Domain Human Motion Recognition using Motion History Information. In: 2003 International Conference on Image Processing, ICIP, 14-17 September, Barcelona,Spain, Vol.2, 321-324.

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Abstract

In this paper we present a system for classifying various human actions in compressed domain video framework. We introduce the notion of quantifying the motion involved, through what we call "motion flow history" (MFH). The encoded motion information readily available in the compressed MPEG stream is used to construct the coarse motion history image (MHI) and the corresponding MFH. The features extracted from the static MHI and MFH compactly characterize the temporal and motion information of the action. Since the features are extracted from the partially decoded sparse motion data, the computational load is minimized to a great extent. The extracted features are used to train the KNN, neural network, SVM and the Bayes classifiers for recognizing a set of seven human actions. Experimental results show that the proposed method efficiently recognizes the set of actions considered.

Item Type:	Conference Paper
Publisher:	IEEE
Additional Information:	�©1990 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Department/Centre:	Division of Electrical Sciences > Electrical Engineering
Date Deposited:	22 Dec 2005
Last Modified:	19 Sep 2010 04:22
URI:	http://eprints.iisc.ac.in/id/eprint/4724

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