A Fully Automatic Player Detection Method Based on One-Class SVM

Xuefeng BAI  Tiejun ZHANG  Chuanjun WANG  Ahmed A. ABD EL-LATIF  Xiamu NIU  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E96-D   No.2   pp.387-391
Publication Date: 2013/02/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.E96.D.387
Print ISSN: 0916-8532
Type of Manuscript: LETTER
Category: Image Recognition, Computer Vision
Keyword: 
player detection,  one-class SVM,  decision-making,  broadcast sports video analysis,  

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Summary: 
Player detection is an important part in sports video analysis. Over the past few years, several learning based detection methods using various supervised two-class techniques have been presented. Although satisfactory results can be obtained, a lot of manual labor is needed to construct the training set. To overcome this drawback, this letter proposes a player detection method based on one-class SVM (OCSVM) using automatically generated training data. The proposed method is evaluated using several video clips captured from World Cup 2010, and experimental results show that our approach achieves a high detection rate while keeping the training set construction's cost low.