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Multiview foreground segmentation using 3D probabilistic model
Gallego Vila, Jaime; Pardàs Feliu, Montse
Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions; Universitat Politècnica de Catalunya. GPI - Grup de Processament d'Imatge i Vídeo
We propose a complete multi-view foreground segmentation and 3D reconstruction system that defines a 3-dimensional probabilistic model to model the foreground object in the 3 spatial dimensions, thus gathering the information from all the camera views. This 3D model is projected to each one of the views in order to perform the 2D segmentation with the foreground information shared by all the cameras. Then, for each one of the views, a MAP-MRF classification framework is applied between the projected region-based foreground model, the pixel-wise background model and the region-based shadow model defined for each view. The resultant masks are used to compute the next 3-dimensional reconstruction. This system achieves correct results by reducing the false positive and false negative errors in sequences where some camera sensors can present camouflage situations between foreground and background. Moreover, the use of the 3D model opens possibilities to use it for objects recognition or human activity understanding.
Peer Reviewed
Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Processament de la imatge i del senyal vídeo
Image processing -- Digital techniques
Three-dimensional display systems
Image classification
Image segmentation
Maximum likelihood estimation
Solid modelling
Imatges -- Processament -- Tècniques digitals
Visualització tridimensional (Informàtica)
Attribution-NonCommercial-NoDerivs 3.0 Spain
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/conferenceObject
Institute of Electrical and Electronics Engineers (IEEE)
         

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