Recognition of human activity through hierarchical stochastic learning
- 23 January 2004
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
Abstract
Seeking to extend the functional capability of the elderly, we explore the use of probabilistic methods to learn and recognise human activity in order to provide monitoring support. We propose a novel approach to learning the hierarchical structure of sequences of human actions through the application of the hierarchical hidden Markov model (HHMM). Experimental results are presented for learning and recognising sequences of typical activities in a home.Keywords
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