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dc.contributor.authorBaiget, Pau
dc.contributor.authorFernández, Carles
dc.contributor.authorRoca, Francesc Xavier
dc.contributor.authorGonzàlez, Jordi
dc.contributor.otherInstitut de Robòtica i Informàtica Industrial
dc.date.accessioned2009-03-13T09:20:53Z
dc.date.available2009-03-13T09:20:53Z
dc.date.created2007
dc.date.issued2007
dc.identifier.citationBaiget, Pau; Fernández, Carles; Roca, F. Xavier; Gonzàlez, Jordi. "Automatic learning of conceptual knowledge in image sequences for human behavior interpretation". 3rd Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA), Girona, Catalunya, 2007. A: Lecture Notes in Computer Science, vol. 4477. Berlin, Alemanya: Springer Verlag, 2007, p. 507-514.
dc.identifier.urihttp://hdl.handle.net/2117/2681
dc.description.abstractThis work describes an approach for the interpretation and explanation of human behavior in image sequences, within the context of a Cognitive Vision System. The information source is the geometrical data obtained by applying tracking algorithms to an image sequence, which is used to generate conceptual data. The spatial characteristics of the scene are automatically extracted from the resuling tracking trajectories obtained during a training period. Interpretation is achieved by means of a rule-based inference engine called Fuzzy Metric Temporal Horn Logic and a behavior modeling tool called Situation Graph Tree. These tools are used to generate conceptual descriptions which semantically describe observed behaviors.
dc.format.extentp. 507-514
dc.language.isoeng
dc.publisherSpringer Verlag
dc.subjectÀrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Processament de la imatge i del senyal vídeo
dc.subject.lcshComputer vision
dc.titleAutomatic learning of conceptual knowledge in image sequences for human behavior interpretation
dc.typePart of book or chapter of book
dc.subject.lemacVisió per ordinador
dc.description.peerreviewedPeer Reviewed
dc.subject.inspecClassificació INSPEC::Pattern recognition::Computer vision
dc.rights.accessOpen Access


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