Computational State Space Models for Activity and Intention Recognition. A Feasibility Study

BACKGROUND: Computational state space models (CSSMs) enable the knowledge-based construction of Bayesian filters for recognizing intentions and reconstructing activities of human protagonists in application domains such as smart environments, assisted living, or security. Computational, i. e., algor...

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Detalles Bibliográficos
Autores principales: Krüger, Frank, Nyolt, Martin, Yordanova, Kristina, Hein, Albert, Kirste, Thomas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4220990/
https://www.ncbi.nlm.nih.gov/pubmed/25372138
http://dx.doi.org/10.1371/journal.pone.0109381

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4220990/
https://www.ncbi.nlm.nih.gov/pubmed/25372138
http://dx.doi.org/10.1371/journal.pone.0109381

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