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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!