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Deterministic and Probabilistic Implementation of Context

Oliver Brdiczka 1 Patrick Reignier 1 James L. Crowley 1 Dominique Vaufreydaz 1 Jérôme Maisonnasse 1
1 PRIMA - Perception, recognition and integration for observation of activity
Inria Grenoble - Rhône-Alpes, UJF - Université Joseph Fourier - Grenoble 1, INPG - Institut National Polytechnique de Grenoble , CNRS - Centre National de la Recherche Scientifique : UMR5217
Abstract : This paper addresses the problem of implementing an abstract context model. First, the abstract context model is represented by a network of situations. Two different implementations for the situation model are then proposed: a deterministic one based on Petri nets and a probabilistic one based on Hidden Markov Models. Both implementations are illustrated and applied to real-world problems.
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Submitted on : Friday, October 3, 2008 - 12:45:48 PM
Last modification on : Tuesday, October 12, 2021 - 2:38:08 PM
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  • HAL Id : inria-00326530, version 1



Oliver Brdiczka, Patrick Reignier, James L. Crowley, Dominique Vaufreydaz, Jérôme Maisonnasse. Deterministic and Probabilistic Implementation of Context. IEEE International Conference on Pervasive Computing and Communications Workshops, Mar 2006, Pisa, Italy. 5 p. ⟨inria-00326530⟩



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