Refractive structure-from-motion through a flat refractive interface
Conference paper
Chadebecq, F., Vasconcelos, F., Dwyer, G., Lacher, R., Ourselin, S., Vercauteren, T. and Stoyanov, D. 2017. Refractive structure-from-motion through a flat refractive interface. 2017 IEEE International Conference on Computer Vision (ICCV). Venice, Italy 22 - 29 Oct 2017 IEEE. pp. 5325-5333 https://doi.org/10.1109/ICCV.2017.568
Type | Conference paper |
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Title | Refractive structure-from-motion through a flat refractive interface |
Authors | Chadebecq, F., Vasconcelos, F., Dwyer, G., Lacher, R., Ourselin, S., Vercauteren, T. and Stoyanov, D. |
Abstract | Recovering 3D scene geometry from underwater images involves the Refractive Structure-from-Motion (RSfM) problem, where the image distortions caused by light refraction at the interface between different propagation media invalidates the single view point assumption. Direct use of the pinhole camera model in RSfM leads to inaccurate camera pose estimation and consequently drift. RSfM methods have been thoroughly studied for the case of a thick glass interface that assumes two refractive interfaces between the camera and the viewed scene. On the other hand, when the camera lens is in direct contact with the water, there is only one refractive interface. By explicitly considering a refractive interface, we develop a succinct derivation of the refractive fundamental matrix in the form of the generalised epipolar constraint for an axial camera. We use the refractive fundamental matrix to refine initial pose estimates obtained by assuming the pinhole model. This strategy allows us to robustly estimate underwater camera poses, where other methods suffer from poor noise-sensitivity. We also formulate a new four view constraint enforcing camera pose consistency along a video which leads us to a novel RSfM framework. For validation we use synthetic data to show the numerical properties of our method and we provide results on real data to demonstrate performance within laboratory settings and for applications in endoscopy. |
Conference | 2017 IEEE International Conference on Computer Vision (ICCV) |
Page range | 5325-5333 |
Proceedings Title | 2017 IEEE International Conference on Computer Vision (ICCV) |
ISSN | |
Electronic | 1550-5499 |
Publisher | IEEE |
Publication dates | |
Online | 25 Dec 2017 |
Publication process dates | |
Accepted | 2017 |
Deposited | 28 Feb 2024 |
Output status | Published |
Digital Object Identifier (DOI) | https://doi.org/10.1109/ICCV.2017.568 |
Web of Science identifier | WOS:000425498405043 |
Language | English |
https://repository.mdx.ac.uk/item/z6589
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