Segmentation of Scenes of Mobile Objects and Demonstrable Backgrounds

  • Frederic Maire
  • Timothy Morris
  • Andry Rakotonirainy

Abstract

In this paper we present a real-time foreground-background segmentation algorithm that exploits the following observation (very often satisfied by a static camera positioned high in its environment). If a blob moves on a pixel p that had not changed its colour significantly for a few frames, then p was probably part of the background when its colour was static. With this information we are able to update differentially pixels believed to be background. This work is relevant to autonomous minirobots, as they often navigate in buildings where smart surveillance cameras could communicate wirelessly with them. A by-product of the proposed system is a mask of the image regions which are demonstrably background. Statistically significant tests show that the proposed method has a better precision and recall rates than the state of the art foreground/background segmentation algorithm of the OpenCV computer vision library.

Keywords

Mobile Robot Local Binary Pattern Background Model Foreground Object Mobile Object 
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 GmbH Berlin Heidelberg 2012

Authors and Affiliations

  • Frederic Maire
    • 1
  • Timothy Morris
    • 2
  • Andry Rakotonirainy
    • 3
  1. 1.FaST QUT and NICTA QRLBrisbaneAustralia
  2. 2.FaST QUTBrisbaneAustralia
  3. 3.CARRS-Q QUTBrisbaneAustralia

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