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Refractive Two-View Reconstruction for Underwater 3D Vision

Authors
  • Chadebecq, François1
  • Vasconcelos, Francisco1
  • Lacher, René1
  • Maneas, Efthymios1
  • Desjardins, Adrien1
  • Ourselin, Sébastien2
  • Vercauteren, Tom2
  • Stoyanov, Danail1
  • 1 Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS),
  • 2 King’s College London,
Type
Published Article
Journal
International Journal of Computer Vision
Publisher
Springer-Verlag
Publication Date
Nov 18, 2019
Volume
128
Issue
5
Pages
1101–1117
Identifiers
DOI: 10.1007/s11263-019-01218-9
PMID: 33343083
PMCID: PMC7738342
Source
PubMed Central
Keywords
License
Unknown

Abstract

Recovering 3D geometry from cameras in underwater applications involves the Refractive Structure-from-Motion problem where the non-linear distortion of light induced by a change of medium density invalidates the single viewpoint assumption. The pinhole-plus-distortion camera projection model suffers from a systematic geometric bias since refractive distortion depends on object distance. This leads to inaccurate camera pose and 3D shape estimation. To account for refraction, it is possible to use the axial camera model or to explicitly consider one or multiple parallel refractive interfaces whose orientations and positions with respect to the camera can be calibrated. Although it has been demonstrated that the refractive camera model is well-suited for underwater imaging, Refractive Structure-from-Motion remains particularly difficult to use in practice when considering the seldom studied case of a camera with a flat refractive interface. Our method applies to the case of underwater imaging systems whose entrance lens is in direct contact with the external medium. By adopting the refractive camera model, we provide a succinct derivation and expression for the refractive fundamental matrix and use this as the basis for a novel two-view reconstruction method for underwater imaging. For validation we use synthetic data to show the numerical properties of our method and we provide results on real data to demonstrate its practical application within laboratory settings and for medical applications in fluid-immersed endoscopy. We demonstrate our approach outperforms classic two-view Structure-from-Motion method relying on the pinhole-plus-distortion camera model.

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