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

PATTERN RECOGNITION

卷:105

Article

Tan-Binh Phan^1,2  Dinh-Hoan Trinh^1,2  Wolf, Didier^1,2  Daul, Christian^1,2 

[1] Univ Lorraine, CRAN, UMR 7039, 2 Ave Foret de Haye, F-54518 Vandoeuvre Les Nancy, France

[2] CNRS, 2 Ave Foret de Haye, F-54518 Vandoeuvre Les Nancy, France

关键词: 3D Image mosaicing;    Structure-from-Motion (SfM);    Dense optical flow;    Endoscopy;    Dermatology;   

DOI  :  10.1016/j.patcog.2020.107391

来源: Elsevier

【 摘 要 】

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. (C) 2020 Elsevier Ltd. All rights reserved.

【 授权许可】

Free