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Context Identification from Video-surveillance Scenes of Multipurpose Halls
Type of publication: Inproceedings
Citation:
Year: 2014
Month: March
Location: Lebanese University, Hadath, Lebanon
Organization: LAAS'14, 27-29.03.2014
Abstract: A novel method for multimodal context identification from video-surveillance footage of multipurpose halls is presented is this paper. After presenting a dedicated definition of ‘Context’ in computer vision systems, the goal is resumed by detecting the active context type among predefined ones. To this end, a spatial modeling of context is performed by extracting five discriminative semantic features according to depth zones. These zones are detected by depth-based scene segmentation method. These features are processed with the Transferable Belief Model (TBM) to propose a classification. Results show the validity of the method for context recognition.
Keywords: context modeling, Pattern Recognition, Transferable Belief Model, Video-surveillance
Authors Charara, Nour
Jarkass, Iman
Maria, Sokhn
Abou Khaled, Omar
Mugellini, Elena
Added by: []
Total mark: 0
Attachments
  • LAAS2014_short paper.pdf
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