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Conference papers

Match Selection and Refinement for Highly Accurate Two-View Structure from Motion

Zhe Liu 1, 2, 3 Pascal Monasse 1, 2, 3 Renaud Marlet 1, 2, 3
3 imagine [Marne-la-Vallée]
LIGM - Laboratoire d'Informatique Gaspard-Monge, CSTB - Centre Scientifique et Technique du Bâtiment, ENPC - École des Ponts ParisTech
Abstract : We present an approach to enhance the accuracy of structure from motion (SfM) in the two-view case. We first answer the question: " fewer data with higher accuracy, or more data with less accuracy? " For this, we establish a relation between SfM errors and a function of the number of matches and their epipolar errors. Using an accuracy estima-tor of individual matches, we then propose a method to select a subset of matches that has a good quality vs. quantity compromise. We also propose a variant of least squares matching to refine match locations based on a focused grid and a multi-scale exploration. Experiments show that both selection and refinement contribute independently to a better accuracy. Their combination reduces errors by a factor of 1.1 to 2.0 for rotation, and 1.6 to 3.8 for translation.
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Contributor : Pascal Monasse <>
Submitted on : Wednesday, July 4, 2018 - 12:10:36 PM
Last modification on : Wednesday, February 3, 2021 - 7:54:27 AM
Long-term archiving on: : Monday, October 1, 2018 - 1:19:50 AM



Zhe Liu, Pascal Monasse, Renaud Marlet. Match Selection and Refinement for Highly Accurate Two-View Structure from Motion. ECCV 2014 ( European Conference on Computer Vision 2014), Sep 2014, Zurich, Switzerland. pp.818-833, ⟨10.1007/978-3-319-10605-2_53⟩. ⟨hal-01153274⟩



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