Temporal Bayesian Networks for Scenario Recognition

  • Ahmed Ziani
  • Cina Motamed
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4522)

Abstract

This work presents an automatic scenario recognition system for video sequence interpretation. The recognition algorithm is based on a Bayesian Networks approach. The model of scenario contains two main layers. The first one enables to highlight atemporal events from the observed visual features. The second layer is focused on the temporal reasoning stage. The temporal layer integrates an event based approach in the framework of the Bayesian Networks. The temporal Bayesian network tracks lifespan of relevant events highlighted from the first layer. Then it estimates qualitative and quantitative relations between temporal events helpful for the recognition task. The global recognition algorithm is illustrated over real indoor images sequences for an abandoned baggage scenario.

Keywords

Visual-surveillance scenario recognition image sequence analysis Bayesian Network 

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Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Ahmed Ziani
    • 1
  • Cina Motamed
    • 1
  1. 1.Laboratoire LASL EA 2600, Université du Littoral Côte d’Opale, Bat 2, 50 Rue F.Buisson, 62228 CalaisFrance

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