Optimal Correspondences from Pairwise Constraints

Olof Enqvist, Klas Josephson, Fredrik Kahl

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceedingpeer-review

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Correspondence problems are of great importance in computer vision. They appear as subtasks in many applications such as object recognition, merging partial 3D reconstructions and image alignment. Automatically matching features from appearance only is difficult and errors are frequent. Thus, it is necessary to use geometric consistency to remove incorrect correspondences. Typically heuristic methods like RANSAC or EM-like algorithms are used, but they risk getting trapped in local optima and are in no way guaranteed to find the best solution. This paper illustrates how pairwise constraints in combination with graph methods can be used to efficiently find optimal correspondences. These ideas are implemented on two basic geometric problems, 3D-3D registration and 2D-3D registration. The developed scheme can handle large rates of outliers and cope with multiple hypotheses. Despite the combinatorial explosion, the resulting algorithm which has been extensively evaluated on real data, yields competitive running times compared to state of the art
Original languageEnglish
Title of host publicationIEEE International Conference on Computer Vision
PublisherIEEE - Institute of Electrical and Electronics Engineers Inc.
Number of pages8
ISBN (Print)978-1-4244-4419-9
Publication statusPublished - 2009
EventIEEE International Conference on Computer Vision (ICCV), 2009 - Kyoto, Japan
Duration: 2009 Sept 272009 Oct 4

Publication series

ISSN (Print)1550-5499


ConferenceIEEE International Conference on Computer Vision (ICCV), 2009

Subject classification (UKÄ)

  • Mathematics
  • Computer Vision and Robotics (Autonomous Systems)

Free keywords

  • Computer Vision
  • Geometry
  • Pairwise Constraints
  • Optimal


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