We describe an algorithm for dining activity analysis in a nursing home. Based on several features, including motion vectors and distance between moving regions in the subspace of...
Alexander G. Hauptmann, Ashok Bharucha, Howard D. ...
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...
— This paper proposes a Hidden Markov Model (HMM) based approach to generate human-like movements for humanoid robots. Given human motion capture data for a class of movements, p...