Gesture Recognition Using a Probabilistic Framework for Pose Matching

Proceedings of the 7th International Conference on Control, Automation, Robotics and Vision, ICARCV 2002

Volumn , Issue , 2002, Pages 763-769

  Elgammal, Ahmed ^a   Shet, Vinay ^a   Yacoob, Yaser ^a   Davis, Larry S ^a  

^a UNIVERSITY OF MARYLAND   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CAMERAS; COMPUTER VISION; DATA REDUCTION; HUMAN COMPUTER INTERACTION; MARKOV PROCESSES; MATHEMATICAL TRANSFORMATIONS; PATTERN MATCHING; PROBABILITY; ALGORITHMS; IMAGE ANALYSIS; IMAGE PROCESSING; INFORMATION ANALYSIS; PROBABILISTIC LOGICS;

BINARY FEATURE; CHAMFER DISTANCE; CHAMFER MATCHING; EDGE MATCHING; DYNAMIC TIME WARPING (DTW); HIDDEN MARKOV MODELS (HMM); MARKOV STOCHASTIC PROCESS; PROBABILISTIC FUNCTIONS; PRT;

GESTURE RECOGNITION;

EID: 2342420424     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (18)

1. Aaron F. Bobick and James W. Davis. The recognition of human movement using temporal templates. IEEE Transactions on Pattern Analysis and Machine Intelligence, 23(3):257-267, 2001.
2. D. Gavrila. Multi-feature hierarchical template matching using distance transforms. In In Proc. of the International Conference on Pattern Recognition, Brisbane, Australia, 1998., pages 439-444.
3. D. Gavrila and V. Philomin. Real-time object detection for "smart" vehicles. In ICCV99, pages 87-93.
4. D. Hogg. Model based vision: A program to see a walking person. Image and Vision Computing, 1(1):5-20, 1983.
5. D. Huttenlocher, and C. Olson R.H. Lilien. View-based recognition using an eigenspace approximation to the hausdorff measure. IEEE Transactions on Pattern Analysis and Machine Intelligence, (9):951-955, 1999.
6. D. Huttenlocher, D. Klanderman, and A. Rucklige. Comparing images using the Hausdorff distance. IEEE Transactions on Pattern Analysis and Machine Intelligence, 15(9):850-863, September 1993.
7. Daniel P. Huttenlocher, Ryan H. Lilien, and Clark F. Olson. Approximate hausdorff matching using eigenspaces. In ARPA Image Understanding Workshop 1996, pages 1181-1186.
8. C. Morimoto, Y. Yacoob, and L. Davis. Recognition of head gestures using hidden markov models international conference on pattern recognition. In International Conference on Pattern Recognition, Vienna, Austria, August 1996, pages 461-465, 1996.
9. C. Olson. A probabilistic formulation for hausdorff matching. In CVPR98, pages 150-156.
10. C. Olson and D. Huttenlocher. Automatic target recognition by matching oriented edge pixels. IEEE Transactions on Image Processing, (1):103-113, 1997.
11. Clark F. Olson. Maximum-likelihood template matching. In IEEE International Conference on Computer Vision and Pattern Recognition, volume 2, pages 52-57, 2000.
12. L. R. Rabiner. A tutorial on hidden markov models and selected applications in speech recognition. Proceedings of the IEEE, 77(2):257-285, February 1989.
13. J. Rehg and T. Kanade. Model-based tracking of self-occluding articulated objects. In ICCV95, pages 612-617, 1995.
14. David W. Scott. Mulivariate Density Estimation. Wiley-Interscience, 1992.
15. T. Starner and A. Pentland. Real-time american sign language recognition from video using hidden markov models. In SCV95, page 5B Systems and Applications, 1995.
16. C. Vogler and D. Metaxas. Adapting hidden markov models for asl recognition by using three-dimensional computer vision methods. In SMC'97., pages 156-161.
17. Christian Vogler and Dimitris N. Metaxas. Parallel hidden markov models for american sign language recognition. In ICCV (1), pages 116-122, 1999.
18. Andrew D. Wilson and Aaron F. Bobick. Parametric hidden markov models for gesture recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, 21(9):884-900, 1999.