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Proceedings Paper

Jersey number detection in sports video for athlete identification
Author(s): Qixiang Ye; Qingming Huang; Shuqiang Jiang; Yang Liu; Wen Gao
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Paper Abstract

Athlete identification is important for sport video content analysis since users often care about the video clips with their preferred athletes. In this paper, we propose a method for athlete identification by combing the segmentation, tracking and recognition procedures into a coarse-to-fine scheme for jersey number (digital characters on sport shirt) detection. Firstly, image segmentation is employed to separate the jersey number regions with its background. And size/pipe-like attributes of digital characters are used to filter out candidates. Then, a K-NN (K nearest neighbor) classifier is employed to classify a candidate into a digit in "0-9" or negative. In the recognition procedure, we use the Zernike moment features, which are invariant to rotation and scale for digital shape recognition. Synthetic training samples with different fonts are used to represent the pattern of digital characters with non-rigid deformation. Once a character candidate is detected, a SSD (smallest square distance)-based tracking procedure is started. The recognition procedure is performed every several frames in the tracking process. After tracking tens of frames, the overall recognition results are combined to determine if a candidate is a true jersey number or not by a voting procedure. Experiments on several types of sports video shows encouraging result.

Paper Details

Date Published: 24 June 2005
PDF: 8 pages
Proc. SPIE 5960, Visual Communications and Image Processing 2005, 59604P (24 June 2005); doi: 10.1117/12.632735
Show Author Affiliations
Qixiang Ye, Institute of Computing Technology (China)
Chinese Academy of Sciences (China)
Qingming Huang, Chinese Academy of Sciences (China)
Shuqiang Jiang, Institute of Computing Technology (China)
Chinese Academy of Sciences (China)
Yang Liu, Harbin Institute of Technology (China)
Wen Gao, Institute of Computing Technology (China)
Chinese Academy of Sciences (China)

Published in SPIE Proceedings Vol. 5960:
Visual Communications and Image Processing 2005
Shipeng Li; Fernando Pereira; Heung-Yeung Shum; Andrew G. Tescher, Editor(s)

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