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Proceedings Paper

Scorebox extraction from mobile sports videos using Support Vector Machines
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Paper Abstract

Scorebox plays an important role in understanding contents of sports videos. However, the tiny scorebox may give the small-display-viewers uncomfortable experience in grasping the game situation. In this paper, we propose a novel framework to extract the scorebox from sports video frames. We first extract candidates by using accumulated intensity and edge information after short learning period. Since there are various types of scoreboxes inserted in sports videos, multiple attributes need to be used for efficient extraction. Based on those attributes, the optimal information gain is computed and top three ranked attributes in terms of information gain are selected as a three-dimensional feature vector for Support Vector Machines (SVM) to distinguish the scorebox from other candidates, such as logos and advertisement boards. The proposed method is tested on various videos of sports games and experimental results show the efficiency and robustness of our proposed method.

Paper Details

Date Published: 15 September 2008
PDF: 9 pages
Proc. SPIE 7073, Applications of Digital Image Processing XXXI, 70730P (15 September 2008); doi: 10.1117/12.797775
Show Author Affiliations
Wonjun Kim, Information and Communications Univ. (Korea, Republic of)
Jimin Park, Information and Communications Univ. (Korea, Republic of)
Changick Kim, Information and Communications Univ. (Korea, Republic of)

Published in SPIE Proceedings Vol. 7073:
Applications of Digital Image Processing XXXI
Andrew G. Tescher, Editor(s)

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