Gesture spotting for low-resolution sports video annotation

Pattern Recognition

Volumn 41, Issue 3, 2008, Pages 1124-1137

  Roh, Myung Cheol ^a   Christmas, Bill ^b   Kittler, Joseph ^b   Lee, Seong Whan ^a  

^a Korea University   (South Korea)

^b UNIVERSITY OF SURREY   (United Kingdom)

Author keywords

Gesture spotting; Low resolution video annotation; Posture descriptor; Posture determination

Indexed keywords

ACOUSTIC NOISE; CAMERAS; MATHEMATICAL MODELS; OPTICAL RESOLVING POWER; VIDEO RECORDING;

GESTURE SPOTTING; LOW RESOLUTION VIDEO ANNOTATION; POSTURE DESCRIPTOR; POSTURE DETERMINATION;

GESTURE RECOGNITION;

EID: 35448984571     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patcog.2007.07.013     Document Type: Article

References (15)

1. W.J. Christmas, A. Kostin, F. Yan, I. Kolonias, J. Kittler, A system for the automatic annotation of tennis matches, Fourth International Workshop on Content based Multimedia Indexing, Riga, June 2005.
2. Yan F., Christmas W., and Kittler J. A tennis ball tracking algorithm for automatic annotation of tennis match. Proceedings of BMVC (September 2005), Oxford, UK 619-628
3. J.R. Wang, N. Parameswaran, Survey of sports video analysis research issues and applications, In: Proceedings of Pan-Sydney Area Workshop on Visual Information Processing, vol. 36, Sydney, Australia, December 2004, pp. 87-90.
4. Sullivan J., and Carlsson S. Recognising and tracking human action. Proceedings of European Conference on Computer Vision (May 2002) 629-644
5. S. Kopf, T. Haenselmann, W. Effelsberg, Shape-base posture and gesture recognition in videos, Electronic Imaging, vol. 5682, San José, CA, January 2005, pp. 114-124.
6. Park A.-Y., and Lee S.-W. Gesture spotting in continuous whole body action sequences using discrete hidden Markov models, gesture in human-computer interaction and simulation. Lect. Notes Artif. Intell. 3881 (May 2006) 100-111
7. M.-C. Roh, H.-K. Shin, S.-W. Lee, S.-W. Lee, Volume motion template for view invariant gesture recognition, in: Proceedings of the 18th IAPR/IEEE International Conference on Pattern Recognition, Hong Kong, China, vol. 2, August 2006, pp. 1229-1232.
8. Ben-Arie J., Wang Z., Pandit P., and Rajaram S. Human activity recognition using multidimensional indexing. IEEE Trans. Pattern Anal. Mach. Intell. 24 8 (2002) 1091-1104
9. Lee H.-K., and Kim J.H. An HMM based threshold model approach for gesture recognition. IEEE Trans. Pattern Anal. Mach. Intell. 21 10 (1999) 961-973
10. Rabiner L., and Juang B.-H. Fundamentals of Speech Recognition (1993), Prentice-Hall, England Chiffs, NJ
11. Oka R. Spotting method for classification of real world data. Comput. J. 41 8 (1998) 559-565
12. J. Alon, V. Athitsos, S. Sclaroff, Accurate and efficient gesture spotting via pruning and subgesture reasoning, In: Proceedings of IEEE Workshop on Human-Computer Interaction, Beijing, China, October (2005) pp. 189-198.
13. M. Irani, P. Anandan, S. Hsu, Mosaic based representations of video sequences and their applications, In: Proceedings of International Conference Computer Vision, MA, USA, June 1995, pp. 605-611.
14. F. Mokhtarian, M. Bober, Curvature Scale Space Representation: Theory, Applications & MPEG-7 Standardisation, Kluwer Academic, Dordrecht, 2003.
15. Fischler M.A., and Bolles R.C. Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Commun ACM 24 (1981) 381-395