Effect of initial HMM choices in multiple sequence training for gesture recognition

International Conference on Information Technology: Coding Computing, ITCC

Volumn 1, Issue , 2004, Pages 608-613

  Liu, Nianjun ^a   Davis, Richard I A ^a   Lovell, Brian C ^a   Kootsookos, Peter J ^a  

^a UNIVERSITY OF QUEENSLAND   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTATIONAL METHODS; IDENTIFICATION (CONTROL SYSTEMS); MARKOV PROCESSES; MATHEMATICAL MODELS; MATRIX ALGEBRA; SET THEORY; SPEECH RECOGNITION;

HANDWRITING RECOGNITION; HIDDEN MARKOV MODELS (HMM); INITIAL MODELS; SEQUENCE TRAINING;

GESTURE RECOGNITION;

EID: 3042694383     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/itcc.2004.1286531     Document Type: Conference Paper

References (11)

1. L.R. Rabiner, and B.H. Juang, Fundamentals of Speech Recognition, New Jersy Prentice Hall, 1993.
2. A. Kundu, Yang He and P. Bahl, "Recognition of Handwritten Words: First and Second Order Hidden Markov Model Based Approach", Pattern Recognition, vol, 22, no. 3, p. 283, 1989.
3. H. Bunke, T. Caelli, "Hidden Markov Models - Applications in Computer Vision", World Scientific Publishing Co, 2001.
4. T.Starner and A.Pentland, "Real-time American Sign Language Recognition", IEEE Transactions On Pattern Analysis and Machine Intelligence, Vol 20.pp 1371-1375, Dec. 1998.
5. Hyeon-Kyu Lee and Jin H. Kim, "An HMM-Based Threshold Model Approach for Gesture Recognition", IEEE Transactions on Pattern Analysis and Machine Intelligence October 1999 (Vol. 21, No. 10). pp. 961-973
6. J. Schlenzig, E. Hunter, and R. Jain. "Recursive identification of gesture inputs using hidden markov models". In IEEE Workshop on Applications of Computer Vision (WACV'94), pages 187-194, 1994.
7. R. I. A. Davis, and B. C. Lovell, and T. Caelli "Improved Estimation of Hidden Markov Model Parameters from Multiple Observation Sequences". Proceedings of the International Conference on Pattern Recognition (ICPR2002), August 11-14 II, pp. 168-171, Quebec City, Canada.
8. R. I. A. Davis and B. C. Lovell, "Comparing and Evaluating HMM Ensemble Training Algorithms Using Train and Test and Condition Number Criteria." To Appear in the Journal of Pattern Analysis and Applications, 2003.
9. D. J. C. Mackay, Ensemble Learning for Hidden Markov Models, Technical report, Cavendish Laboratory, University of Cambridge, UK, 1997.
10. A. Stolcke and S. Omohundro, "Hidden Markov Model induction by Bayesian model mergin", Advances in Neural Information Processing Systems, pp. 11-18, Morgan Kaufmann, San Mateo, United States of America, CA1993.
11. Nianjun Liu, Brian C. Lovell and Peter J. Kootsookos, "Evaluation of HMM training algorithms for Letter Hand Gesture Recognition", Proceedings of IEEE International Symposium on Signal Processing and Information Technology. December 14-17, 2003, Darmstadt, Germany. Accepted, In Press.