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ELIS – Multimedia Lab
Optimization of Automated Video Surveillance Using Multi-modal Video AnalysisViktor Slavkovikj
05/12/2012
Viktor Slavkovikj
Multimedia LabDepartment of Electronics and Information Systems
Faculty of Enginering and ArchitectureGhent University – iMinds
promotors: prof. dr. ir. Rik Van de Walle, dr. ir. Sofie Van Hoecke
Optimization of automated video surveillance using multi-modal video
analysis
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ELIS – Multimedia Lab
Optimization of Automated Video Surveillance Using Multi-modal Video AnalysisViktor Slavkovikj
05/12/2012
Outline
• Introduction• Methodology and Goals• Challenges
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ELIS – Multimedia Lab
Optimization of Automated Video Surveillance Using Multi-modal Video AnalysisViktor Slavkovikj
05/12/2012
• Automated surveillance deals with observation of people and objects in complex environments
• Multiple application purposes: detection, tracking, recognition, motion analysis, activity understanding.
Introduction
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ELIS – Multimedia Lab
Optimization of Automated Video Surveillance Using Multi-modal Video AnalysisViktor Slavkovikj
05/12/2012
• Most automatic surveillance systems use only color information
• Due to noise, the accuracy of color video surveillance is impaired in some situations
• Our goal is to obtain improved accuracy by using multiple/different sensor modalities
Methodology and Goals
rgb image depth map
+
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ELIS – Multimedia Lab
Optimization of Automated Video Surveillance Using Multi-modal Video AnalysisViktor Slavkovikj
05/12/2012
• Different capture sensors provide different types of output data
• Synchronization, registration, correlation of the different outputs
• Handling the complexity of the increased quantity of data efficiently
Challenges
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ELIS – Multimedia Lab
Optimization of Automated Video Surveillance Using Multi-modal Video AnalysisViktor Slavkovikj
05/12/2012
Thank you for your attention!