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Pedestrian Tracking from a Moving Host Using Corner Points

  • Mirko Meuter
  • Dennis Müller
  • Stefan Müller-Schneiders
  • Uri Iurgel
  • Su-Birm Park
  • Anton Kummert
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4842)

Abstract

We present a new camera based algorithm to track pedestrians from a moving host using corner points. The algorithm can handle partial shape variations and the set of point movement vectors allows to estimate not only translation but also scaling. The algorithm works as follows: Corner points are extracted within a bounding box, where the pedestrian is detected in the current frame and in a search region in the next frame. We compare the local neighbourhood of points to find point correspondences using an improved method. The point correspondences are used to estimate the object movement using a translation scale model. A fast iterative outlier removal strategy is employed to remove single false point matches. A correction step is presented to correct the position estimate. The step uses the accumulated movement of each point over time to detect outliers that can not be found using inter-frame motion vectors. First tests indicate a good performance of the presented tracking algorithm, which is improved by the presented correction step.

Keywords

Corner Point Interest Point Search Region Correction Step Point Trajectory 
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 2007

Authors and Affiliations

  • Mirko Meuter
    • 1
  • Dennis Müller
    • 2
  • Stefan Müller-Schneiders
    • 2
  • Uri Iurgel
    • 2
  • Su-Birm Park
    • 2
  • Anton Kummert
    • 1
  1. 1.Faculty of Electrical Information and Media Engineering, University of Wuppertal, D-42119 WuppertalGermany
  2. 2.Delphi Delco Electronics Europe, Advanced Engineering, D-42119 WuppertalGermany

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