A fuzzy qualitative approach to human motion recognition

IEEE International Conference on Fuzzy Systems

Volumn , Issue , 2008, Pages 1242-1249

  Chan, Chee Seng ^a   Liu, Honghai ^a   Brown, David ^a   Kubota, Naoyuki ^b  

^a UNIVERSITY OF PORTSMOUTH   (United Kingdom)

^b TOKYO METROPOLITAN UNIVERSITY   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

FUZZY LOGIC; FUZZY SYSTEMS; KINEMATICS; MARKOV PROCESSES; MATHEMATICAL TRANSFORMATIONS; MECHANICS; ROBOTICS; ROBOTS;

ACTIVITY REPRESENTATIONS; ANATOMICAL LANDMARKS; BODY SEGMENTS; COMPLICATED TASKS; HUMAN MOTION RECOGNITIONS; HUMAN MOTIONS; IMAGE SEQUENCES; MOTION DATABASES; MOTION OF RIGID BODIES; QUALITATIVE APPROACHES; QUALITATIVE STATES; QUANTISATION; RECOGNITION RATES; ROBOT KINEMATICS; STATE TRANSITIONS; SYMBOLIC REPRESENTATIONS; TRACKING ALGORITHMS; TRAINING DATUMS;

HIDDEN MARKOV MODELS;

EID: 55249088767     PISSN: 10987584     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/FUZZY.2008.4630530     Document Type: Conference Paper

References (22)

1. M. Blank, L. Gorelick, E. Shechhnan, M. Irani, and R. Basri, Action as space-time shapes. In Proceedings of IEEE International Conference on Computer Vision, volume 2, pages 1395-1402, Beijing. China. 2005.
2. A. Bobick and A. Wilson, A state-based technique for the summarization and recognition of gesture. In Proceeding of the International Conference on Computer Vision, pages 382-388, 1995.
3. M. Brand, N. Oliver, and A. Pentland. Coupled hidden markov models for complex action recognition. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pages 994-999, 1997.
4. H. Buxton. Learning and understanding dyanmic scene activity. Image and Vision Computing, 21(1): 125-136, 2003.
5. L. Campbell and A. Bobick. Recognition of human body motion using phase space constraints. In Proceedings of the Fifth International Conference on Computer Vision, pages 624-630, Washington, DC, USA, 1995.
6. C. S. Chan, H. Liu, and D. Brown, Recognition of human motion from qualitative normalised templates. Journal of Intelligent and Robotic Systems, 48(1):79-95, January 2007.
7. M. Isard and A. Blake, Condensation: Conditional density propagation for visual tracking. International Journal of Computeter Vision, 29(1):5-28, 1998.
8. G. Johansson. Visual motion perception. Scientific American, 232(6):76-88, 1975.
9. H. Liu, D. Brown, and G. Coghill. Fuzzy qualitative robot kinematics (in press). IEEE Transactions on Fuzzy Systems. 2007.
10. H. Liu and G. Coghill. Fuzzy qualitative trigonometry. In Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, volume II, pages 1291-1296, Hawaii. USA, 2005.
11. K. Murakami and H. Taguchi, Gesture recognition using recurrent neural networks. In Proceedings of the SIGCHI conference on Human factors in computing systems, pages 237-242, ACM Press. 1991.
12. R. M. Murray, S. Shastry, Z. Li, and S. S. Sastry, A Mathematical Introduction to Robotic Manipulation. CRC Press. 1994.
13. K. Oliver, B. Rosario, and A. Pentland. A bayeslan computer system for modeling human interactions. IEEE Transactions on Pattern Analysis and Machine Intellingence, 22(8):831-843, 2000.
14. H. Qiang and C. Debrunner, Individual recognition from periodic activty using hidden markov models. In Proceedings of the Workshop on Human Motion, pages 47-52, 2000.
15. L. Rabiner, A tutorial on hidden markov models and selected applications in speech recognition. Proceedings of the IEEE. 77(2):257-284, February 1989.
16. C. Schuldt, I. Laptev, and B. Caputo, Recognizing human actions: A local svm approach. In Proceedings of the International Conference on Pattern Recognition, volume 3, pages 32-36, Hong Kong, 2004.
17. Q. Shen and R. Leitch, Combining qualitative simulation and fuzzy sets. Recent advances in qualitative physics, pages 83-100, 1993.
18. Q. Shen and R. Leitch, Fuzzy qualitative simulation. IEEE Transactions on Systems, Man and Cybernetics, 23(4): 1038-1061, Jul/Aug 1993.
19. H. Sidenbladh, M. Black, and D. Fleet, Stochastic tracking of 3d human figures using 2d image motion. In Proceedings of the 6th European Conference on Computer Vision, number II, pages 702-718, London, UK, 2000, Springer-Verlag.
20. A. Sundaresan, R. Chellappa, and A. Roy Chowdhury, Multiple view tracking of humans modelled by kinematic chains. In Proceedings of the International Conference on Image Processing, volume 2, pages 1009-1012, Singapore, 2004.
21. A. Wilson and A. Bobick, Parametric hidden markov models for gesture recognition. IEEE Transaction on Pattern Analysis and Machine Intelligence, 21(9):884-900, 1999.
22. J. Yamato, J. Ohya, and K. Ishii, Recognizing human action in time-sequential images using hidden markov model. In Proceedings of the 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pages 379-385, 1992.