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A Non-parametric Approach to Detect Changes in Aerial Images

  • Marco Túlio Alves RodriguesEmail author
  • Daniel Balbino
  • Erickson Rangel Nascimento
  • William Robson Schwartz
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9423)

Abstract

Detecting changes in aerial images acquired from a scene at different times, possibly with different cameras and at different view points, is a crucial step for many image processing and computer vision applications, such as remote sensing, visual surveillance and civil infrastructure. In this paper, we propose a novel approach to automatically detect changes based on local descriptors and a non-parametric image block modeling. Differently from most approaches, which are pixel-based, our approach combines contextual information and kernel density estimation to model the image regions to identify changes. The experimental results show the effectiveness of the proposed approach compared to other methods in the literature, demonstrating the robustness of our algorithm. The results also demonstrate that the approach can be employed to generate a summary containing mostly frames presenting significant changes.

Keywords

Change detection Non-parametric modeling Aerial images 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Marco Túlio Alves Rodrigues
    • 1
    Email author
  • Daniel Balbino
    • 1
  • Erickson Rangel Nascimento
    • 1
  • William Robson Schwartz
    • 1
  1. 1.Department of Computer ScienceUniversidade Federal de Minas GeraisBelo HorizonteBrazil

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