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

Authors:
Gi Hyun Lim;Byoungjun Chung;Il Hong Suh
Affiliations:
Hanyang University, Seoul, South Korea;Hanyang University, Seoul, South Korea;Hanyang University, Seoul, South Korea
Venue:
Proceedings of the 6th international conference on Human-robot interaction
Year:
2011

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Abstract

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.