Learning structures of interval-based Bayesian networks in probabilistic generative model for human complex activity recognition

Pattern Recognition, Volume 81, 2018, Pages 545-561.

Cited by: 26|Bibtex|Views16
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Other Links: dblp.uni-trier.de|academic.microsoft.com

Abstract:

Abstract Complex activity recognition is challenging due to the inherent uncertainty and diversity of performing a complex activity. Normally, each instance of a complex activity has its own configuration of atomic actions and their temporal dependencies. In our previous work, we proposed an atomic action-based Bayesian model that const...More

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