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Multiple player tracking in soccer videos: an adaptive multiscale sampling approach

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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.

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Acknowledgements

This research is supported by Ministry of Culture, Sports and Tourism (MCST) and Korea Creative Content Agency (KOCCA) in the Culture Technology (CT) Research & Development Program 2016 (R2016030044, Development of Context-Based Sport Video Analysis, Summarization, and Retrieval Technologies).

Author information

Correspondence to Chanho Jung.

Additional information

Communicated by C. Xu.

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Supplementary material 1 (avi 18533 KB)

Supplementary material 1 (avi 18533 KB)

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Cite this article

Kim, W., Moon, S., Lee, J. et al. Multiple player tracking in soccer videos: an adaptive multiscale sampling approach. Multimedia Systems 24, 611–623 (2018) doi:10.1007/s00530-018-0586-9

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Keywords

  • Multiple object tracking
  • Moving objects
  • Multiscale sampling
  • Online interpolation