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3D model acquisition from extended image sequences

  • Paul Beardsley
  • Phil Torr
  • Andrew Zisserman
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1065)

Abstract

A method for matching image primitives through a sequence is described, for the purpose of acquiring 3D geometric models. The method includes a novel robust estimator of the trifocal tensor, based on a minimum number of token correspondences across an image triplet; and a novel tracking algorithm in which corners and line segments are matched over image triplets in an integrated framework. The matching techniques are both robust (detecting and discarding mismatches) and fully automatic.

The matched tokens are used to compute 3D structure, which is initialised as it appears and then recursively updated over time. The approach is uncalibrated — camera internal parameters and camera motion are not known or required.

Experimental results are provided for a variety of scenes, including outdoor scenes taken with a hand-held camcorder. Quantitative statistics are included to assess the matching performance, and renderings of the 3D structure enable a qualitative assessment of the results.

Keywords

Fundamental Matrix Robust Computation Epipolar Line Epipolar Geometry Outdoor Scene 
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 1996

Authors and Affiliations

  • Paul Beardsley
    • 1
  • Phil Torr
    • 1
  • Andrew Zisserman
    • 1
  1. 1.Dept of Engineering ScienceUniversity of OxfordOxford

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