Factored state-abstract hidden Markov models for activity recognition using pervasive multi-modal sensors
Current probabilistic models for activity recognition do not incorporate much sensory input data due to the problem of state space explosion. In this paper, we propose a model for activity recognition, called the Factored State-Abtract Hidden Markov Model (FS-AHMM) to allow us to integrate many sens...
| Main Authors: | , , , |
|---|---|
| Other Authors: | |
| Format: | Conference Paper |
| Published: |
IEEE Computer Society Press
2005
|
| Online Access: | http://hdl.handle.net/20.500.11937/11457 |