Title
Multiple player tracking in soccer videos: an adaptive multiscale sampling approach.
Abstract
Visual tracking is an essential technique in computer vision. Even though the notable improvement has been achieved during last few years, tracking multiple objects still remains as a challenging task. In this paper, a novel method for tracking multiple players in soccer videos, which include severe occlusions between players and nonlinear motions by their complex interactions, is introduced. Specifically, we first extract moving objects (i.e., players) by refining results of background subtraction via the edge information obtained from the frame differencing result. Then, we conduct multiscale sampling in foreground regions, which are spatially close to each tracked player, and subsequently computing the dissimilarity between sampled image blocks and each tracked player. Based on the best-matched case, the state of each tracked player (e.g., center position, color, etc.) is consistently updated using the online interpolation scheme. Experimental results in various soccer videos show the efficiency and robustness of our method compared to previous approaches introduced in the literature.
Year
DOI
Venue
2018
10.1007/s00530-018-0586-9
Multimedia Syst.
Keywords
Field
DocType
Multiple object tracking,Moving objects,Multiscale sampling,Online interpolation
Background subtraction,Computer vision,Nonlinear system,Computer science,Interpolation,Real-time computing,Robustness (computer science),Eye tracking,Artificial intelligence,Sampling (statistics)
Journal
Volume
Issue
ISSN
24
6
0942-4962
Citations 
PageRank 
References 
1
0.36
29
Authors
5
Name
Order
Citations
PageRank
Wonjun Kim130126.50
Sung-Won Moon210.36
Ji-Won Lee311612.82
Do-Won Nam421.38
Chanho Jung522413.83