13 December 2021. Monday. 3PM. London Time.
Hybrid (zoom and face-to-face). Room Colln CG15. Fully Online over Zoom because of omicron.
Title Refractive Two-View Reconstruction for Underwater 3D Vision
Speaker François Chadabecq, Department of Computer Science, Middlesex University, London
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.
Bio Since September 2021, François Chadebecq is a Lecturer in Computer Science at Middlesex University London and an Honorary Research Fellow at UCL. François obtained a PhD degree in Computer Vision from Université Clermont Auvergne. His research focus is in AI and specifically computer vision for Computer-Assisted Intervention in Minimally-Invasive Surgery. The underlying theoretical contributions of his work is geometric and photometric vision modelling with an application focus on vision-based metrology, 3D reconstruction and navigation for endoscopy as well as image-guided intervention.
Meeting ID: 668 413 8396