ICASSP 2006, 31st IEEE International Conference on Acoustics, Speech, and Signal Processing, May 14-19, 2006, Toulouse, France
In this paper, we propose a new type of multi-dimensional Hidden Markov Model based on the idea of Dependency Tree between positions. This simplification leads to an efficient implementation of the re-estimation algorithms, while keeping a mix of horizontal and vertical dependencies between positions. We explain DT-HMM and we present the formulas for the Maximum Likelihood re-estimation. We illustrate the algorithm by training a 2-dimensional model on a set of coherent images.
Type:
Conference
City:
Toulouse
Date:
2006-05-14
Department:
Data Science
Eurecom Ref:
1968
Copyright:
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