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

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概要

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• 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.

著者

• A. ABD

  Mathematics Department, Faculty of Science, Menoufia University

• BAI Xuefeng

  Shenzhen Graduate School, Harbin Institute of Technology

• ZHANG Tiejun

  School of Computer Science and Technology, Harbin Institute of Technology

• WANG Chuanjun

  Shenzhen Graduate School, Harbin Institute of Technology

• NIU Xiamu

  Shenzhen Graduate School, Harbin Institute of Technology

関連論文

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

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