Hidden Markov models for spatio-temporal pattern recognition

Lovell, Brian C. and Caelli, Terry (2005). Hidden Markov models for spatio-temporal pattern recognition. In C. H. Chen and P. S. P. Wang (Ed.), Handbook of pattern recognition and computer vision 3rd ed. (pp. 1-16) Singapore: World Scientific Publications.

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Author Lovell, Brian C.
Caelli, Terry
Title of chapter Hidden Markov models for spatio-temporal pattern recognition
Title of book Handbook of pattern recognition and computer vision
Place of Publication Singapore
Publisher World Scientific Publications
Publication year 2005
Sub-type Critical scholarly text
Edition 3rd
Editor C. H. Chen
P. S. P. Wang
ISBN 9812561056; 9789812561053
Chapter number 1
Start page 1
End page 16
Total pages 16
Total chapters 33
Collection year 2005
Language eng
Subjects 280208 Computer Vision
280203 Image Processing
280104 Computer-Human Interaction
280207 Pattern Recognition
B1
700199 Computer software and services not elsewhere classified
Abstract/Summary The success of many real-world applications demonstrates that hidden Markov models(HMMs) are highly effective in one-dimensional pattern recognition problems such as speech recognition. Research is now focussed on extending HMMs to 2-D and possibly 3-D applications which arise in gesture, face, and handwriting recognition. Although the HMM has become a major workhorse of the pattern recognition community, there are few analytical results which can explain its remarkably good pattern recognition performance. There are also only a few theoretical principles for guiding researchers in selecting topologies or understanding how the model parameters contribute to performance. In this chapter, we deal with these issues and use simulated data to evaluate the performance of a number of alternatives to the traditional Baum-Welch algorithm for learning HMM parameters. We then compare the best of these strategies to Baum-Welch on a real hand gesture recognition system in an attempt to develop insights into these fundamental aspects of learning.
Keyword Iris-research
Gesture recognition
Face recognition
Handwriting recognition
Pattern analysis
Q-Index Code B1
Q-Index Status Provisional Code
Institutional Status UQ
 
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Created: Tue, 11 Jan 2005, 10:00:00 EST by Brian C. Lovell on behalf of School of Information Technol and Elec Engineering  -  Detailed History