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Extending Interrupted Feature Point Tracking for 3-D Affine Reconstruction

  • Yasuyuki Sugaya
  • Kenichi Kanatani
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3021)

Abstract

Feature point tracking over a video sequence fails when the points go out of the field of view or behind other objects. In this paper, we extend such interrupted tracking by imposing the constraint that under the affine camera model all feature trajectories should be in an affine space. Our method consists of iterations for optimally extending the trajectories and for optimally estimating the affine space, coupled with an outlier removal process. Using real video images, we demonstrate that our method can restore a sufficient number of trajectories for detailed 3-D reconstruction.

Keywords

Camera Model Motion Segmentation Outlier Removal Subspace Separation Complete 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 2004

Authors and Affiliations

  • Yasuyuki Sugaya
    • 1
  • Kenichi Kanatani
    • 1
  1. 1.Depertment of Information TechnologyOkayama UniversityOkayamaJapan

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