Reconstruction from Uncalibrated Sequences with a Hierarchy of Trifocal Tensors

  • David Nistér
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1842)


This paper considers projective reconstruction with a hierarchical computational structure of trifocal tensors that integrates feature tracking and geometrical validation of the feature tracks. The algorithm was embedded into a system aimed at completely automatic Euclidean reconstruction from uncalibrated handheld amateur video sequences. The algorithm was tested as part of this system on a number of sequences grabbed directly from a low-end video camera without editing. The proposed approach can be considered a generalisation of a scheme of [Fitzgibbon and Zisserman, ECCV ’98]. The proposed scheme tries to adapt itself to the motion and frame rate in the sequence by finding good triplets of views from which accurate and unique trifocal tensors can be calculated. This is in contrast to the assumption that three consecutive views in the video sequence are a good choice. Using trifocal tensors with a wider span suppresses error accumulation and makes the scheme less reliant on bundle adjustment. The proposed computational structure may also be used with fundamental matrices as the basic building block.


Line Triple Bundle Adjustment Sweet Spot Structure From Motion Projective Reconstruction 
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 2000

Authors and Affiliations

  • David Nistér
    • 1
  1. 1.Visual TechnologyEricsson ResearchEricsson Radio SystemsStockholmSweden

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