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Recognition and incremental learning of scenario-oriented human behavior patterns by two threshold models

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3 Author(s)
Gi Hyun Lim ; Department of Electronics and Computer Engineering, Hanyang University, Seoul, Korea ; Byoungjun Chung ; Il Hong Suh

Two HMM-based threshold models are suggested for recognition and incremental learning of scenario-oriented human behavior patterns. One is the expected behavior threshold model to discriminate if a monitored behavior pattern is normal or not. The other model is the registered behavior threshold model to detect whether such behavior pattern is already learned. If a behavior patten is detected as a new one, an HMM is generated to represent the pattern, and then the HMM is used to update behavior clusters by hierarchical clustering process.

Published in:

2011 6th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

Date of Conference:

8-11 March 2011