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Robust multiple cue fusion-based high-speed and nonrigid object tracking algorithm for short track speed skating

[+] Author Affiliations
Chenguang Liu, Heng-Da Cheng, Yuxuan Wang, Min Xian

Utah State University, Computer Science Department, 4205 Old Main Hill, Logan, Utah 84322-4205, United States

Yingtao Zhang

Harbin Institute of Technology, Department of Computer Science and Technology, 92 Xidazhi Street, Harbin 150001, China

J. Electron. Imaging. 25(1), 013014 (Jan 25, 2016). doi:10.1117/1.JEI.25.1.013014
History: Received July 7, 2015; Accepted December 1, 2015
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Abstract.  This paper presents a methodology for tracking multiple skaters in short track speed skating competitions. Nonrigid skaters move at high speed with severe occlusions happening frequently among them. The camera is panned quickly in order to capture the skaters in a large and dynamic scene. To automatically track the skaters and precisely output their trajectories becomes a challenging task in object tracking. We employ the global rink information to compensate camera motion and obtain the global spatial information of skaters, utilize random forest to fuse multiple cues and predict the blob of each skater, and finally apply a silhouette- and edge-based template-matching and blob-evolving method to labelling pixels to a skater. The effectiveness and robustness of the proposed method are verified through thorough experiments.

© 2016 SPIE and IS&T

Citation

Chenguang Liu ; Heng-Da Cheng ; Yingtao Zhang ; Yuxuan Wang and Min Xian
"Robust multiple cue fusion-based high-speed and nonrigid object tracking algorithm for short track speed skating", J. Electron. Imaging. 25(1), 013014 (Jan 25, 2016). ; http://dx.doi.org/10.1117/1.JEI.25.1.013014


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