Fast Bayesian people detection

Authors
Publication date 2010
Journal BNAIC
Event 22nd Benelux Conference on Artificial Intelligence (BNAIC 2010), Luxembourg
Volume | Issue number 22
Organisations
  • Faculty of Science (FNWI) - Informatics Institute (IVI)
Abstract Template-based methods have been shown to be effective at solving the problem of tracking specific objects, but their large number of free parameters can make them slow to apply and hard to optimise globally. In this work, we propose a template-based method for tracking people with fixed cameras, which automatically detects the number of people in a frame, is robust to occlusions, and can run at near-real-time frame rates. We demonstrate the effectiveness of the method by comparing it to a state-of-the-art background segmentation algorithm and show its important performance advantage.
Document type Article
Note Proceedings title: Proceedings of the 22nd Benelux Conference on Artificial Intelligence (BNAIC 2010)
Language English
Published at http://bnaic2010.uni.lu/Papers/Category%20A/Englebienne.pdf
Permalink to this page
Back