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Wood Detection and Tracking in Videos of Rivers

  • Imtiaz Ali
  • Julien Mille
  • Laure Tougne
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6688)

Abstract

Rivers during floods bring a lot of fallen trees and debris. Video surveillance systems are installed on strategically important places on the rivers. To protect these places from destructions due to accumulation of wood, such systems must be able to automatically detect wood. Image segmentation is performed to separate wood and other moving elements from the rest of the water. Moving objects are detected with respect to brightness and temporal variation features. The floating wood is then tracked in the sequence of frames by temporal linking of the segments generated in the detection step. Our algorithm is tested on multiple videos of floods and the results are evaluated both qualitatively and quantitatively.

Keywords

Image Segmentation Gaussian Mixture Model Water Wave Consecutive Frame Representative Point 
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 2011

Authors and Affiliations

  • Imtiaz Ali
    • 1
    • 2
  • Julien Mille
    • 1
    • 3
  • Laure Tougne
    • 1
    • 2
  1. 1.Université de Lyon, CNRSFrance
  2. 2.LIRIS, UMR5205Université Lyon 2France
  3. 3.LIRIS, UMR5205Université Lyon 1France

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