Lightweight Object Tracking in Compressed Video Streams Demonstrated in Region-of-Interest Coding
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Research Article Lightweight Object Tracking in Compressed Video Streams Demonstrated in Region-of-Interest Coding Robbie De Sutter,1 Koen De Wolf,1 Sam Lerouge,2 and Rik Van de Walle1 1 Multimedia
Lab, Department of Electronics and Information Systems, Ghent University - IBBT, Sint-Pietersnieuwstraat 41, B-9000 Ghent, Belgium 2 Regionale Media Maatschappij, Kwadestraat 151b, B-8800 Roeselare, Belgium Received 25 January 2006; Revised 28 September 2006; Accepted 11 October 2006 Recommended by Dimitrios Tzovaras Video scalability is a recent video coding technology that allows content providers to offer multiple quality versions from a single encoded video file in order to target different kinds of end-user devices and networks. One form of scalability utilizes the regionof-interest concept, that is, the possibility to mark objects or zones within the video as more important than the surrounding area. The scalable video coder ensures that these regions-of-interest are received by an end-user device before the surrounding area and preferably in higher quality. In this paper, novel algorithms are presented making it possible to automatically track the marked objects in the regions of interest. Our methods detect the overall motion of a designated object by retrieving the motion vectors calculated during the motion estimation step of the video encoder. Using this knowledge, the region-of-interest is translated, thus following the objects within. Furthermore, the proposed algorithms allow adequate resizing of the region-of-interest. By using the available information from the video encoder, object tracking can be done in the compressed domain and is suitable for real-time and streaming applications. A time-complexity analysis is given for the algorithms proving the low complexity thereof and the usability for real-time applications. The proposed object tracking methods are generic and can be applied to any codec that calculates the motion vector field. In this paper, the algorithms are implemented within MPEG-4 fine-granularity scalability codec. Different tests on different video sequences are performed to evaluate the accuracy of the methods. Our novel algorithms achieve a precision up to 96.4%. Copyright © 2007 Robbie De Sutter et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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INTRODUCTION
Video content providers want to target as many kinds of enduser devices without the need to create a large simulstore of multiple versions of the same video fragment. As a consequence, recent video encoding techniques embed scalability such that multiple versions of an encoded video can be derived on the fly, that is, without the need for decoding and reencoding the video. Within the Moving Picture Experts Group (MPEG), the fine-granularity scalability (FGS) technology was developed to add scalability to the MPEG video coding technologies. The FGS technology c
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