Parallel tracking of all soccer players by integrating detected positions in multiple view images

Sachiko Iwase, Hideo Saito

Research output: Chapter in Book/Report/Conference proceedingConference contribution

66 Citations (Scopus)

Abstract

Soccer, one of the popular sports around the world, is often broadcasted on TV, and various researches have done on soccer scene images such as strategy analysis, scene recovery, automatic indexing of soccer scenes, and automatic intelligent sports casting. As robust player tracking is fundamental to those researches, there is a demand for an automatic player tracking system using soccer imaging data. In this paper, we propose a method of tracking soccer players using multiple views. Tracking is done by integrating the tracking data from all cameras, using the geometrical relationship between cameras called homography. Integrating information from all cameras enables stable tracking on the scene, where the tracking by a single camera often fails in the case of occlusion.

Original languageEnglish
Title of host publicationProceedings of the 17th International Conference on Pattern Recognition, ICPR 2004
EditorsJ. Kittler, M. Petrou, M. Nixon
Pages751-754
Number of pages4
DOIs
Publication statusPublished - 2004 Dec 20
EventProceedings of the 17th International Conference on Pattern Recognition, ICPR 2004 - Cambridge, United Kingdom
Duration: 2004 Aug 232004 Aug 26

Publication series

NameProceedings - International Conference on Pattern Recognition
Volume4
ISSN (Print)1051-4651

Other

OtherProceedings of the 17th International Conference on Pattern Recognition, ICPR 2004
CountryUnited Kingdom
CityCambridge
Period04/8/2304/8/26

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ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

Cite this

Iwase, S., & Saito, H. (2004). Parallel tracking of all soccer players by integrating detected positions in multiple view images. In J. Kittler, M. Petrou, & M. Nixon (Eds.), Proceedings of the 17th International Conference on Pattern Recognition, ICPR 2004 (pp. 751-754). (Proceedings - International Conference on Pattern Recognition; Vol. 4). https://doi.org/10.1109/ICPR.2004.1333881