Periodic human motion description for sports video databases

Many different visual features can be used for analysis and annotation of sports video material. Here, we present a periodic motion feature descriptor that can discriminate between different sports types that contain periodic motion. The experimental results, using video material from the 1992 Barcelona Olympic Games, show that the proposed periodic motion descriptor can successfully classify four sports types: sprint, long-distance running, hurdling and canoeing.

[1]  Fred Stentiford,et al.  Recent Trends in Video Analysis: A Taxonomy of Video Classification Problems , 2002, IMSA.

[2]  Charles R. Dyer,et al.  Cyclic motion detection using spatiotemporal surfaces and curves , 1990, [1990] Proceedings. 10th International Conference on Pattern Recognition.

[3]  William J. Christmas,et al.  Recognising human running behaviour in sports video sequences , 2002, Object recognition supported by user interaction for service robots.

[4]  Roger D. Boyle,et al.  Tracking multiple sports players through occlusion, congestion and scale , 2001, BMVC.

[5]  Zhu Liu,et al.  Multimedia content analysis-using both audio and visual clues , 2000, IEEE Signal Process. Mag..

[6]  Jiri Matas,et al.  Colour-based object recognition for video annotation , 2002, Object recognition supported by user interaction for service robots.

[7]  Randal C. Nelson,et al.  Detecting activities , 1993, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[8]  Aaron F. Bobick,et al.  Visual recognition of multi-agent action using binary temporal relations , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).

[9]  Patrick Pérez,et al.  Statistical motion-based video indexing and retrieval , 2000, RIAO.

[10]  Fang Liu,et al.  Finding periodicity in space and time , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[11]  A. Spanias,et al.  An adaptive modified covariance algorithm for spectral analysis , 1996, Proceedings of 8th Workshop on Statistical Signal and Array Processing.

[12]  Tsuhan Chen,et al.  Audio Feature Extraction and Analysis for Scene Segmentation and Classification , 1998, J. VLSI Signal Process..

[13]  William J. Christmas,et al.  Defining quantisation strategies and a perceptual similarity measure for texture-based annotation and retrieval , 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

[14]  Randal C. Nelson,et al.  Detection and Recognition of Periodic, Nonrigid Motion , 1997, International Journal of Computer Vision.

[15]  Hironobu Fujiyoshi,et al.  Real-time human motion analysis by image skeletonization , 1998, Proceedings Fourth IEEE Workshop on Applications of Computer Vision. WACV'98 (Cat. No.98EX201).

[16]  Stanislav Kovacic,et al.  Tracking People in Sport: Making Use of Partially Controlled Environment , 2001, CAIP.

[17]  Christian Wöhler,et al.  Motion-based recognition of pedestrians , 1998, Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170).