Image Analysis and Processing, International Conference on (2003)
Sept. 17, 2003 to Sept. 19, 2003
Terry Caelli , University of Alberta
Brendan McCane , University of Otago
Hidden Markov models (HMMs) have become a standard tool for pattern recognition in computer vision. Although parameter and topology estimation have been studied, and still are, detailed analysis of how these estimated parameters contribute to HMM performance is rarely addressed. In this paper we develop tools for measuring such contributions and illustrate key issues in a representative task of gesture recognition — 3D motion recovery from 2D projections.
T. Caelli and B. McCane, "Component Analysis of Hidden Markov Models in Computer Vision," Image Analysis and Processing, International Conference on(ICIAP), Mantova, Italy, 2003, pp. 510.