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Adaptive Background Modeling for Land and Water Composition Scenes

  • Jing Zhao
  • Shaoning PangEmail author
  • Bruce Hartill
  • AbdolHossein Sarrafzadeh
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9280)

Abstract

In the context of maritime boat ramps surveillance, this paper proposes an Adaptive Background Modeling method for Land and Water composition scenes (ABM-lw) to interpret the traffic of boats passing across boat ramps. We compute an adaptive learning rate to account for changes on land and water composition scenes, in which the portion of water changes over time due to tidal dynamics and other environmental influences. Experimental comparative tests and quantitative performance evaluations of real-world boat-flow monitoring traffic sequences demonstrate the benefits of the proposed algorithm.

Keywords

Learning Rate Background Modeling Tidal Height Move Object Detection Luminance Threshold 
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 International Publishing Switzerland 2015

Authors and Affiliations

  • Jing Zhao
    • 1
  • Shaoning Pang
    • 1
    Email author
  • Bruce Hartill
    • 2
  • AbdolHossein Sarrafzadeh
    • 1
  1. 1.Unitec Institute of TechnologyAucklandNew Zealand
  2. 2.National Institute of Water and Atmospheric ResearchAucklandNew Zealand

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