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Proceedings Paper

Framework for tracking and analysis of soccer video
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Paper Abstract

In this paper, we present a complete framework for automatic analysis of soccer video by using domain specific information. In the proposed framework, following shot boundary detection, soccer shots are classified into 3 classes using the ratio of grass-colored pixels in a frame, and the size and number of soccer objects detected in a shot. These classes are long shots, in-field medium shots, and others, such as out-of-field of close-up shots. The long shots and in-field medium shots are further processed to analyze their semantic content. We observe that different low-level processing algorithms may be required to process different shot classes. For example, we introduce different tracking algorithms for the long shots and in- field medium shots. Furthermore, frame registration onto a reference field model is not usually applicable to in-field medium shots, because the field lines may not be visible. The proposed framework enables development of more effective low-level processing algorithms for high-level scene understanding, which perform nearly in real time. The results show the increased accuracy and efficiency of the proposed methods.

Paper Details

Date Published: 4 January 2002
PDF: 12 pages
Proc. SPIE 4671, Visual Communications and Image Processing 2002, (4 January 2002); doi: 10.1117/12.453120
Show Author Affiliations
Ahmet Ekin, Univ. of Rochester (United States)
A. Murat Tekalp, Univ. of Rochester (United States)

Published in SPIE Proceedings Vol. 4671:
Visual Communications and Image Processing 2002
C.-C. Jay Kuo, Editor(s)

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