A Memory Architecture and Contextual Reasoning Framework for Cognitive Vision

  • J. Kittler
  • W. J. Christmas
  • A. Kostin
  • F. Yan
  • I. Kolonias
  • D. Windridge
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3540)

Abstract

One of the key requirements for a cognitive vision system to support reasoning is the possession of an effective mechanism to exploit context both for scene interpretation and for action planning. Context can be used effectively provided the system is endowed with a conducive memory architecture that supports contextual reasoning at all levels of processing, as well as a contextual reasoning framework. In this paper we describe a unified apparatus for reasoning using context, cast in a Bayesian reasoning framework. We also describe a modular memory architecture developed as part of the VAMPIRE* vision system which allows the system to store raw video data at the lowest level and its semantic annotation of monotonically increasing abstraction at the higher levels. By way of illustration, we use as an application for the memory system the automatic annotation of a tennis match.

Keywords

Memory Architecture Tennis Ball Reasoning Engine Contextual Reasoning Foreground Image 
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-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • J. Kittler
    • 1
  • W. J. Christmas
    • 1
  • A. Kostin
    • 1
  • F. Yan
    • 1
  • I. Kolonias
    • 1
  • D. Windridge
    • 1
  1. 1.Centre for Vision, Speech and Signal ProcessingUniversity of SurreyGuildfordUK

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