An efficient algorithm for modelling duration in hidden Markov models, with a dramatic application

被引：1

作者：

Hauberg, Soren ^{[1
]}

Sloth, Jakob ^{[1
]}

机构：

[1] Univ Copenhagen, Dept Comp Sci, Copenhagen, Denmark

来源：

JOURNAL OF MATHEMATICAL IMAGING AND VISION | 2008年 / 31卷 / 2-3期

关键词：

hidden Markov models; modelling duration; filtering; optimal particle filters; theatrical play;

D O I：

10.1007/s10851-007-0059-9

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

For many years, the hidden Markov model (HMM) has been one of the most popular tools for analysing sequential data. One frequently used special case is the left-right model, in which the order of the hidden states is known. If knowledge of the duration of a state is available it is not possible to represent it explicitly with an HMM. Methods for modelling duration with HMM's do exist (Rabiner in Proc. IEEE 77(2):257-286, [1989]), but they come at the price of increased computational complexity. Here we present an efficient and robust algorithm for modelling duration in HMM's, and this algorithm is successfully used to control autonomous computer actors in a theatrical play.

引用

页码：165 / 170

页数：6

共 8 条

[1]

Bishop C. M., 2006, Pattern Recognition and Machine Learning, P179

[2] The recognition of human movement using temporal templates [J].