%0 Journal Article
%T Determining the Best Suited Semantic Events for Cognitive Surveillance
%A Carles Fernandez
%A Pau Baiget
%A Xavier Roca
%A Jordi Gonzalez
%J Expert Systems with Applications
%D 2011
%V 38
%N 4
%I Elsevier
%F Carles Fernandez2011
%O ISE
%O exported from refbase (http://refbase.cvc.uab.es/show.php?record=1722), last updated on Tue, 18 Nov 2014 09:49:27 +0100
%X State-of-the-art systems on cognitive surveillance identify and describe complex events in selected domains, thus providing end-users with tools to easily access the contents of massive video footage. Nevertheless, as the complexity of events increases in semantics and the types of indoor/outdoor scenarios diversify, it becomes difficult to assess which events describe better the scene, and how to model them at a pixel level to fulfill natural language requests. We present an ontology-based methodology that guides the identification, step-by-step modeling, and generalization of the most relevant events to a specific domain. Our approach considers three steps: (1) end-users provide textual evidence from surveilled video sequences; (2) transcriptions are analyzed top-down to build the knowledge bases for event description; and (3) the obtained models are used to generalize event detection to different image sequences from the surveillance domain. This framework produces user-oriented knowledge that improves on existing advanced interfaces for video indexing and retrieval, by determining the best suited events for video understanding according to end-users. We have conducted experiments with outdoor and indoor scenes showing thefts, chases, and vandalism, demonstrating the feasibility and generalization of this proposal.
%K Cognitive surveillance
%K Event modeling
%K Content-based video retrieval
%K Ontologies
%K Advanced user interfaces
%U http://refbase.cvc.uab.es/files/FBR2011a.pdf
%U http://dx.doi.org/10.1016/j.eswa.2010.09.070
%P 4068–4079