Skip to Main content Skip to Navigation
Journal articles

Optical flow-based structure-from-motion for the reconstruction of epithelial surfaces

Abstract : This paper details a novel optical flow-based structure from motion (SfM) approach for the reconstruction of surfaces with few textures using video sequences acquired under strong illumination changes. An original image search and grouping strategy allows to reconstruct each 3D scene point using a large set of 2D homologous points extracted from a reference image and its superimposed images acquired from different viewpoints. A variational optical flow scheme with a descriptor-based data term leads to a robust, accurate and dense homologous point determination between the image pairs. Thus, contrary to classical SfM usable for textured scenes, the proposed dense point cloud reconstruction algorithm requires neither a feature point tracking method nor any multi-view stereo technique. The performance of the proposed SfM approach is assessed on phantoms with known ground truth and on very complex patient data of various medical examinations and image modalities.
Document type :
Journal articles
Complete list of metadata
Contributor : Accord Elsevier CCSD Connect in order to contact the contributor
Submitted on : Friday, May 20, 2022 - 11:19:44 AM
Last modification on : Friday, June 3, 2022 - 3:35:10 AM


Files produced by the author(s)


Distributed under a Creative Commons Attribution - NonCommercial 4.0 International License




Tan-Binh Phan, Dinh-Hoan Trinh, Didier Wolf, Christian Daul. Optical flow-based structure-from-motion for the reconstruction of epithelial surfaces. Pattern Recognition, Elsevier, 2020, 105, pp.107391. ⟨10.1016/j.patcog.2020.107391⟩. ⟨hal-02666537⟩



Record views


Files downloads