Layered models for context awareness
US7203635B2 · kind B2 · utility
72Cited by
34References
42Claims
0Family size
Assignee
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Key dates
| Filing date | Jun 27, 2002 |
| Grant date | Apr 10, 2007 |
| Priority date | — |
| Expiry date | Oct 5, 2024 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG10L25/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The present invention relates to a system and methodology providing layered probabilistic representations for sensing, learning, and inference from multiple sensory streams at multiple levels of temporal granularity and abstraction. The methods facilitate robustness to subtle changes in environment and enable model adaptation with minimal retraining. An architecture of Layered Hidden Markov Models (LHMMs) can be employed having parameters learned from stream data and at different periods of time, wherein inferences can be determined relating to context and activity from perceptual signals.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.