title: Tracking of ball and players in beach volleyball videos.
abstract: This paper presents methods for the determination of players' positions and contact time points by tracking the players and the ball in beach volleyball videos. Two player tracking methods are compared, a classical particle filter and a rigid grid integral histogram tracker. Due to mutual occlusion of the players and the camera perspective, results are best for the front players, with 74,6% and 82,6% of correctly tracked frames for the particle method and the integral histogram method, respectively. Results suggest an improved robustness against player confusion between different particle sets when tracking with a rigid grid approach. Faster processing and less player confusions make this method superior to the classical particle filter. Two different ball tracking methods are used that detect ball candidates from movement difference images using a background subtraction algorithm. Ball trajectories are estimated and interpolated from parabolic flight equations. The tracking accuracy of the ball is 54,2% for the trajectory growth method and 42,1% for the Hough line detection method. Tracking results of over 90% from the literature could not be confirmed. Ball contact frames were estimated from parabolic trajectory intersection, resulting in 48,9% of correctly estimated ball contact points.
authors.affiliation: Digital Sports Group, Pattern Recognition Lab, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany.
authors.forename: Gabriel
authors.initials: G
authors.lastname: Gomez
authors.affiliation: Departamento de Ingeniería de Telecomunicación, Universidad Politécnica de Madrid, Madrid, Spain.
authors.forename: Patricia
authors.initials: P
authors.lastname: Herrera López
authors.affiliation: Department of Training Science and Sport Informatics, Technische Universität München, Munich, Germany.
authors.forename: Daniel
authors.initials: D
authors.lastname: Link
authors.affiliation: Digital Sports Group, Pattern Recognition Lab, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany.
authors.forename: Bjoern
authors.initials: B
authors.lastname: Eskofier
mesh_terms: D000465:Algorithms; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D007899:Leisure Activities; D008297:Male; D009043:Motor Activity / Q000502:physiology; D009068:Movement / Q000502:physiology; D014741:Video Recording / Q000295:instrumentation / Q000379:methods / Q000706:statistics & numerical data*; D054798:Volleyball; D055815:Young Adult