Video Object Segmentation: A Compressed Domain Approach

Babu, RV and Ramakrishnan, KR and Srinivasan, SH (2004) Video Object Segmentation: A Compressed Domain Approach. In: IEEE Transactions On Circuits And Systems For Video Technology, 14 (4). pp. 462-474.

PDF 92.pdf - Published Version Restricted to Registered users only Download (1MB) | Request a copy

Abstract

This paper addresses the problem of extracting video objects from MPEG compressed video. The,only cues used for object segmentation are the motion vectors which are sparse in MPEG. A method for automatically estimating the number of objects and extracting independently moving video objects using Motion vectors is presented here. First, the motion vectors are accumulated over a few frames to enhance the motion information, which are further spatially interpolated to get dense motion vectors. The final segmentation, using the dense motion vectors, is obtained by applying the expectation maximization (EM) algorithm. A block-based affine clustering method is proposed for determining the number of appropriate motion models to be used for the EM step and the segmented objects are temporally tracked to obtain the video objects. Finally, a strategy for edge refinement is proposed to, extract the,precise object boundaries. Illustrative examples are provided to demonstrate the efficacy of the approach. A prominent application of the proposed method is that of object-based coding, which is part of the MPEG-4 standard.

Item Type:	Journal Article
Publication:	IEEE Transactions On Circuits And Systems For Video Technology
Publisher:	IEEE.
Additional Information:	Copyright of this article belongs to IEEE. "YEAR IEEE. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Raman Research Institute's's products or services. Internal or 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 must be obtained from the IEEE by writing to ubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it."
Keywords:	Compressed domain, expectation maximization (EM) algorithm;motion segmentation;MPEG-4;object segmentation;tracking;video object planes.
Department/Centre:	Division of Electrical Sciences > Electrical Engineering
Date Deposited:	19 Dec 2008 19:25
Last Modified:	19 Sep 2010 04:56
URI:	http://eprints.iisc.ac.in/id/eprint/17384

Actions (login required)

View Item