This paper presents a novel approach for adaptive online multi-stroke sketch recognition based on Hidden Markov Model (HMM). The method views the drawing sketch as the result of a ...
A self-adaptive Hidden Markov Model (SA-HMM) based framework is proposed for behavior recognition in this paper. In this model, if an unknown sequence cannot be classified into an...
Hidden Markov Models (HMMs) are important tools for modeling sequence data. However, they are restricted to discrete latent states, and are largely restricted to Gaussian and disc...
Le Song, Sajid M. Siddiqi, Geoffrey J. Gordon, Ale...
The Asynchronous Hidden Markov Model (AHMM) models the joint likelihood of two observation sequences, even if the streams are not synchronised. We explain this concept and how the...
Marc Al-Hames, Claus Lenz, Stephan Reiter, Joachim...
Identifying effective tutorial strategies is a key problem for tutorial dialogue systems research. Ongoing work in human-human tutorial dialogue continues to reveal the complex phe...
Kristy Elizabeth Boyer, Eunyoung Ha, Michael D. Wa...