Commentary Paper 3 on Visual Players Detection and Tracking in Soccer Matches

Author

Malik, Hafiz

Author_Institution

Electr. & Comput. Eng. Dept., Univ. of Michigan-Dearborn, Dearborn, MI, USA

fYear

2008

fDate

1-3 Sept. 2008

Firstpage

337

Lastpage

338

Abstract

This manuscript presents object detection and tracking in video clips of soccer matches. Background subtraction based framework on pixel energy is proposed to detect objects in the input video clip with varying light conditions, high frame rates, and real-time processing. Unsupervised clustering is then used classify detected objects into various classes. A stochastic approach based on maximum a posteriori probability (MAP) is proposed for object tracking.

Keywords

maximum likelihood estimation; object detection; pattern clustering; sport; unsupervised learning; video signal processing; background subtraction; maximum a posteriori probability; object detection; object tracking; player tracking; soccer matches; stochastic approach; unsupervised clustering; visual players detection; Computer vision; Equations; Games; Object detection; Parameter estimation; Performance analysis; Power engineering and energy; Stochastic processes; Surveillance; Videoconference;

fLanguage

English

Publisher

ieee

Conference_Titel

Advanced Video and Signal Based Surveillance, 2008. AVSS '08. IEEE Fifth International Conference on

Conference_Location

Santa Fe, NM

Print_ISBN

978-0-7695-3341-4

Electronic_ISBN

978-0-7695-3422-0

Type

conf

DOI

10.1109/AVSS.2008.79

Filename

4730437