Towards a Semi-automatic Situation Diagnosis System in Surveillance Tasks

  • José Mira
  • Rafael Martínez
  • Mariano Rincón
  • Margarita Bachiller
  • Antonio Fernández-Caballero
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4528)


This paper describes an ongoing project that develops a set of generic components to help humans (semi-automatic system) in surveillance and security tasks in several scenarios. These components are based in the computational model of a set of selective and Active VISual Attention mechanisms with learning capacity (AVISA) and in the superposition of an “intelligence” layer that incorporates the knowledge of human experts in security tasks. The project described integrates the responses of these alert mechanisms in the synthesis of the three basic subtasks present in any surveillance and security activity: real-time monitoring, situation diagnosing, and action planning and control. In order to augment the diversity of environments and situations where AVISA system may be used, as well as its efficiency as support to surveillance tasks, knowledge components derived from situating cameras on mobile platforms are also developed.


Human Expert Human Activity Recognition State Transition Diagram Selective Visual Attention Video Event 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • José Mira
    • 1
  • Rafael Martínez
    • 1
  • Mariano Rincón
    • 1
  • Margarita Bachiller
    • 1
  • Antonio Fernández-Caballero
    • 2
  1. 1.E.T.S.I. Informática - Univ. Nacional de Educación a Distancia, MadridSpain
  2. 2.Escuela Politécnica Superior de Albacete & Instituto de Investigación en Informática de Albacete, Universidad Castilla-La Mancha, AlbaceteSpain

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