By Topic

A novel ball detection framework for real soccer video

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Xinguo Yu ; Infocomm Res. Inst., Singapore, Singapore ; Qi Tian ; Kong Wah Wan

Despite a lot of research efforts in sports video analysis, soccer video indexing remains a challenging task due to the lack of structure in a soccer game that could help in structure analysis. In particular, little work was done in detecting and tracking the ball whose trajectory could play a crucial role for detecting key events. We propose a novel framework for accurately detecting the ball for broadcast soccer video. Our framework combines both direct and indirect insights to identify the ball rather than conventional simple template matching methods. It has three key components. First we infer the ball size range from the player size. Next non-ball objects are removed to reduce the possible ball candidates. Last but not least, a Kalman filer-based procedure mines candidate trajectories in candidate feature images. Then, a procedure selects the reliable ball trajectories from them. The experimental results on two 1000-frame sequences confirm that the proposed framework is very effective and obtain a better result than existing methods.

Published in:

Multimedia and Expo, 2003. ICME '03. Proceedings. 2003 International Conference on  (Volume:2 )

Date of Conference:

6-9 July 2003