1. 1/6 ELIS – Multimedia Lab Optimization of Automated Video Surveillance Using Multi-modal Video Analysis Viktor Slavkovikj 05/12/2012 Viktor Slavkovikj Multimedia Lab Department of Electronics and Information Systems Faculty of Enginering and Architecture Ghent 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

2. 2/6 ELIS – Multimedia Lab Optimization of Automated Video Surveillance Using Multi-modal Video Analysis Viktor Slavkovikj 05/12/2012 Outline Introduction Methodology and Goals Challenges

3. 3/6 ELIS – Multimedia Lab Optimization of Automated Video Surveillance Using Multi-modal Video Analysis Viktor 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

4. 4/6 ELIS – Multimedia Lab Optimization of Automated Video Surveillance Using Multi-modal Video Analysis Viktor 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 +

5. 5/6 ELIS – Multimedia Lab Optimization of Automated Video Surveillance Using Multi-modal Video Analysis Viktor 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

6. 6/6 ELIS – Multimedia Lab Optimization of Automated Video Surveillance Using Multi-modal Video Analysis Viktor Slavkovikj 05/12/2012 Thank you for your attention!