Abstract
3D position tracking of the ball plays a crucial role in professional volleyball analysis. In volleyball games, the constraint conditions that limit the performance of the ball tracking include the fast irregular movement of the ball, the small-size of the ball, the complex background as well as the occlusion problem caused by players. This paper proposes a ball size adaptive (BSA) tracking window, a ball feature likelihood model and an anti-occlusion likelihood measurement (AOLM) base on Particle Filter for improving the accuracy. By adaptively changing the tracking windows according to the ball size, it is possible to track the ball with changing size in different video images. On the other hand, the ball feature likelihood enables to track stably even in complex background. Furthermore, AOLM based on a multiple-camera system solves the occlusion problems since it can eliminate the low likelihood caused by occlusion. Experimental results which are based on the HDTV video sequences (2014 Inter High School Games of Men’s Volleyball) captured by four cameras located at the corners of the court show that the success rate of the ball’s 3D position tracking achieves 93.39 %.
| Original language | English |
|---|---|
| Pages (from-to) | 203-211 |
| Number of pages | 9 |
| Journal | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
| Volume | 9314 |
| DOIs | |
| Publication status | Published - 2015 |
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Keywords
- 3D position tracking
- Ball feature
- Likelihood model
- Particle filter
- Volleyball analysis
ASJC Scopus subject areas
- Theoretical Computer Science
- Computer Science(all)
Cite this
Particle filter with ball size adaptive tracking window and ball feature likelihood model for ball’s 3D position tracking in volleyball analysis. / Cheng, Xina; Zhuang, Xizhou; Wang, Yuan; Honda, Masaaki; Ikenaga, Takeshi.
In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 9314, 2015, p. 203-211.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Particle filter with ball size adaptive tracking window and ball feature likelihood model for ball’s 3D position tracking in volleyball analysis
AU - Cheng, Xina
AU - Zhuang, Xizhou
AU - Wang, Yuan
AU - Honda, Masaaki
AU - Ikenaga, Takeshi
PY - 2015
Y1 - 2015
N2 - 3D position tracking of the ball plays a crucial role in professional volleyball analysis. In volleyball games, the constraint conditions that limit the performance of the ball tracking include the fast irregular movement of the ball, the small-size of the ball, the complex background as well as the occlusion problem caused by players. This paper proposes a ball size adaptive (BSA) tracking window, a ball feature likelihood model and an anti-occlusion likelihood measurement (AOLM) base on Particle Filter for improving the accuracy. By adaptively changing the tracking windows according to the ball size, it is possible to track the ball with changing size in different video images. On the other hand, the ball feature likelihood enables to track stably even in complex background. Furthermore, AOLM based on a multiple-camera system solves the occlusion problems since it can eliminate the low likelihood caused by occlusion. Experimental results which are based on the HDTV video sequences (2014 Inter High School Games of Men’s Volleyball) captured by four cameras located at the corners of the court show that the success rate of the ball’s 3D position tracking achieves 93.39 %.
AB - 3D position tracking of the ball plays a crucial role in professional volleyball analysis. In volleyball games, the constraint conditions that limit the performance of the ball tracking include the fast irregular movement of the ball, the small-size of the ball, the complex background as well as the occlusion problem caused by players. This paper proposes a ball size adaptive (BSA) tracking window, a ball feature likelihood model and an anti-occlusion likelihood measurement (AOLM) base on Particle Filter for improving the accuracy. By adaptively changing the tracking windows according to the ball size, it is possible to track the ball with changing size in different video images. On the other hand, the ball feature likelihood enables to track stably even in complex background. Furthermore, AOLM based on a multiple-camera system solves the occlusion problems since it can eliminate the low likelihood caused by occlusion. Experimental results which are based on the HDTV video sequences (2014 Inter High School Games of Men’s Volleyball) captured by four cameras located at the corners of the court show that the success rate of the ball’s 3D position tracking achieves 93.39 %.
KW - 3D position tracking
KW - Ball feature
KW - Likelihood model
KW - Particle filter
KW - Volleyball analysis
UR - http://www.scopus.com/inward/record.url?scp=84984638534&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84984638534&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-24075-6_20
DO - 10.1007/978-3-319-24075-6_20
M3 - Article
AN - SCOPUS:84984638534
VL - 9314
SP - 203
EP - 211
JO - Lecture Notes in Computer Science
JF - Lecture Notes in Computer Science
SN - 0302-9743
ER -