Video Understanding Framework For Automatic Behavior Recognition

LES AUTEURS François Bremond, Monique Thonnat, Marcos Zuniga


We propose an activity monitoring framework based on a platform called VSIP, enabling
behavior recognition in different environments. To allow end-users to actively participate in the
development of a new application, VSIP separates algorithms from a priori knowledge. For
describing how VSIP works, we present a full description of a system developed with this
platform for recognizing behaviors, involving either isolated individual, group of people or
crowds, in the context of visual monitoring of metro scenes using multiple cameras. In this
work, we also illustrate the capability of the framework to easily combine and tune various
recognition methods dedicated to the visual analysis of specific situations (e.g. mono/multi
actors activities, numerical/symbolic actions or temporal scenarios). We also present other
applications using this framework, in the context of behavior recognition. VSIP has shown a
good performance on human behavior recognition for different problems and configurations,
being suitable to fulfill a large variety of requirements.

Mots clé: video understanding, behavior recognition, activity monitoring

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BibTeX reference:

author =       {Francois Bremond and Monique Thonnat and Marcos Zuniga},
title =        {Video Understanding Framework For Automatic Behavior Recognition},
journal =      {Behavior Research Methods},
year =         {2006},
volume =       {3},
number =       {38},
pages =        {416-426},

Dernière mise à jour : 7/11/06