Moving Object Detection from Mobile Platforms Using Stereo Data Registration

  • Angel D. Sappa
  • David Gerónimo
  • Fadi Dornaika
  • Mohammad Rouhani
  • Antonio M. López
Part of the Studies in Computational Intelligence book series (SCI, volume 386)


This chapter describes a robust approach for detecting moving objects from on-board stereo vision systems. It relies on a feature point quaternion-based registration, which avoids common problems that appear when computationally expensive iterative-based algorithms are used on dynamic environments. The proposed approach consists of three main stages. Initially, feature points are extracted and tracked through consecutive 2D frames. Then, a RANSAC based approach is used for registering two point sets, with known correspondences in the 3D space. The computed 3D rigid displacement is used to map two consecutive 3D point clouds into the same coordinate system by means of the quaternion method. Finally, moving objects correspond to those areas with large 3D registration errors. Experimental results show the viability of the proposed approach to detect moving objects like vehicles or pedestrians in different urban scenarios.


Object Detection Camera Motion Mobile Platform Consecutive Frame Iterative Close 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 Berlin Heidelberg 2012

Authors and Affiliations

  • Angel D. Sappa
    • 1
  • David Gerónimo
    • 1
    • 2
  • Fadi Dornaika
    • 3
    • 4
  • Mohammad Rouhani
    • 1
  • Antonio M. López
    • 1
    • 2
  1. 1.Computer Vision CenterUniversitat Autònoma de BarcelonaBarcelonaSpain
  2. 2.Computer Science DepartmentUniversitat Autònoma de BarcelonaBarcelonaSpain
  3. 3.University of the Basque CountrySan SebastianSpain
  4. 4.IKERBASQUE, Basque Foundation for ScienceBilbaoSpain

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