Visual Tracking of Athletes in Beach Volleyball Using a Single Camera

This paper aims at successful tracking of beach volleyball athletes during competition using only a single camera. Due to the wide range of possible motions and non-rigid shape changes, the tracking task becomes quite complex. We propose a novel method based on integral histograms, to use a high dimensional model for a particle filter without drastic increase in runtime. We extend integral histograms to handle rotated objects. Additionally to the tracking process, a segmentation of the lower body parts enables generating real world player positions from a single camera view. Comparisons to hand annotated position data revealed sufficient accuracy for classical sport scientific purposes. The paper focuses on beach volleyball but the proposed methods can be utilized in other sports and non sports applications.

[1]  Martin J. Johnson,et al.  Real-time Computation of Haar-like features at generic angles for detection algorithms , 2006 .

[2]  Horst Bischof,et al.  Fast Approximated SIFT , 2006, ACCV.

[3]  James J. Little,et al.  A Boosted Particle Filter: Multitarget Detection and Tracking , 2004, ECCV.

[4]  Matej Kristan,et al.  Towards fast and efficient methods for tracking players in sports , 2006 .

[5]  Abdesselam Bouzerdoum,et al.  Skin segmentation using color pixel classification: analysis and comparison , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[6]  V. Di Salvo,et al.  Performance Characteristics According to Playing Position in Elite Soccer , 2006, International journal of sports medicine.

[7]  Thomas Mauthner,et al.  A Robust Multiple Object Tracking for Sport Applications , 2007 .

[8]  Bernhard P. Wrobel,et al.  Multiple View Geometry in Computer Vision , 2001 .

[9]  Rainer Lienhart,et al.  An extended set of Haar-like features for rapid object detection , 2002, Proceedings. International Conference on Image Processing.

[10]  T. Reilly A motion analysis of work-rate in different positional roles in professional football match-play , 1976 .

[11]  P. Krustrup,et al.  Physical and metabolic demands of training and match-play in the elite football player , 2006, Journal of sports sciences.

[12]  Patrick Pérez,et al.  Data fusion for visual tracking with particles , 2004, Proceedings of the IEEE.

[13]  Markus Tilp,et al.  Digital game analysis in beach volleyball. , 2006 .

[14]  Ian M. Franks,et al.  How to Develop a Notation System , 2004, Essentials of Performance Analysis in Sport.

[15]  William J. Christmas,et al.  A Tennis Ball Tracking Algorithm for Automatic Annotation of Tennis Match , 2005, BMVC.

[16]  Fatih Murat Porikli,et al.  Integral histogram: a fast way to extract histograms in Cartesian spaces , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[17]  Neil J. Gordon,et al.  A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking , 2002, IEEE Trans. Signal Process..

[18]  Patrick Pérez,et al.  Color-Based Probabilistic Tracking , 2002, ECCV.

[19]  Ian M. Franks,et al.  Notational Analysis of Sport , 2004 .

[20]  Michael Isard,et al.  CONDENSATION—Conditional Density Propagation for Visual Tracking , 1998, International Journal of Computer Vision.

[21]  Ian M. Franks,et al.  The use of feedback-based technologies , 2004 .