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CVIU
2004

Layered representations for learning and inferring office activity from multiple sensory channels

8 years 7 months ago
Layered representations for learning and inferring office activity from multiple sensory channels
We present the use of layered probabilistic representations for modeling human activities, and describe how we use the representation to do sensing, learning, and inference at multiple f temporal granularity and abstraction and from heterogeneous data sources. The approach centers on the use of a cascade of Hidden Markov Models named Layered Hidden Markov Models (LHMMs) to diagnose states of a user
Nuria Oliver, Ashutosh Garg, Eric Horvitz
Added 17 Dec 2010
Updated 17 Dec 2010
Type Journal
Year 2004
Where CVIU
Authors Nuria Oliver, Ashutosh Garg, Eric Horvitz
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