DocumentCode :
1411516
Title :
Multiple Player Tracking in Sports Video: A Dual-Mode Two-Way Bayesian Inference Approach With Progressive Observation Modeling
Author :
Xing, Junliang ; Ai, Haizhou ; Liu, Liwei ; Lao, Shihong
Author_Institution :
Dept. of Comput. Sci. & Technol., Tsinghua Univ., Beijing, China
Volume :
20
Issue :
6
fYear :
2011
fDate :
6/1/2011 12:00:00 AM
Firstpage :
1652
Lastpage :
1667
Abstract :
Multiple object tracking (MOT) is a very challenging task yet of fundamental importance for many practical applications. In this paper, we focus on the problem of tracking multiple players in sports video which is even more difficult due to the abrupt movements of players and their complex interactions. To handle the difficulties in this problem, we present a new MOT algorithm which contributes both in the observation modeling level and in the tracking strategy level. For the observation modeling, we develop a progressive observation modeling process that is able to provide strong tracking observations and greatly facilitate the tracking task. For the tracking strategy, we propose a dual-mode two-way Bayesian inference approach which dynamically switches between an offline general model and an online dedicated model to deal with single isolated object tracking and multiple occluded object tracking integrally by forward filtering and backward smoothing. Extensive experiments on different kinds of sports videos, including football, basketball, as well as hockey, demonstrate the effectiveness and efficiency of the proposed method.
Keywords :
inference mechanisms; object detection; object tracking; sport; backward smoothing; dual-mode two-way Bayesian inference approach; forward filtering; multiple object tracking algorithm; multiple occluded object tracking; multiple player tracking; object detection; offline general model; online dedicated model; progressive observation modeling; single isolated object tracking; sports video; Bayesian methods; Detectors; Image color analysis; Robustness; Shape; Target tracking; Bayesian inference; object detection; object tracking; observation modeling; sports video; Algorithms; Artificial Intelligence; Bayes Theorem; Biometry; Computer Simulation; Image Enhancement; Image Interpretation, Computer-Assisted; Models, Statistical; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity; Sports; Video Recording; Whole Body Imaging;
fLanguage :
English
Journal_Title :
Image Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1057-7149
Type :
jour
DOI :
10.1109/TIP.2010.2102045
Filename :
5674086
Link To Document :
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