By Topic

Automatic Detection and Analysis of Player Action in Moving Background Sports Video Sequences

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
$33 $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

5 Author(s)
Haojie Li ; School of Software, Dalian University of Technology, Dalian, China ; Jinhui Tang ; Si Wu ; Yongdong Zhang
more authors

This paper presents a system for automatically detecting and analyzing complex player actions in moving background sports video sequences, aiming at action-based sports videos indexing and providing kinematic measurements for coach assistance and performance improvement. The system works in a coarse-to-fine fashion. For an input video, in the coarse granularity level, we automatically segment the highlights, that is, the video clips containing the desired action as summaries for general user viewing purposes; in the middle granularity level, we recognize the action types to support action-based video indexing and retrieval; and finally in the fine granularity level, the critical kinematic parameters of player action are obtained for sports professionals' training purposes. However, the complex and dynamic background of sports videos and the complexity of player actions bring considerable difficulty to the automatic analysis. To fulfill such a challenging task, robust algorithms including global motion estimation with adaptive outliers filtering, object segmentation based on adaptive background construction, and automatic human body tracking are proposed in this paper. Two visual analyzing tools: motion panorama and overlay composition, are also introduced. Real diving and jump game videos are used to test the proposed system and algorithms, and the extensive and encouraging experimental results show their effectiveness.

Published in:

IEEE Transactions on Circuits and Systems for Video Technology  (Volume:20 ,  Issue: 3 )