TL;DR
This paper introduces EdgeGraph3D, a novel system for reconstructing both straight and curved 3D edges from unordered image sequences, enhancing multi-view stereo surface accuracy especially under challenging lighting conditions.
Contribution
The work presents a new graph-based 2D edge representation and integrates it into a multi-view stereo pipeline, enabling 3D edge reconstruction beyond straight lines and points.
Findings
Effective in strong illumination changes and reflections
Improves surface reconstruction accuracy
Works with unordered image sequences
Abstract
This paper presents a novel method for the reconstruction of 3D edges in multi-view stereo scenarios. Previous research in the field typically relied on video sequences and limited the reconstruction process to either straight line-segments, or edge-points, i.e., 3D points that correspond to image edges. We instead propose a system, denoted as EdgeGraph3D, able to recover both straight and curved 3D edges from an unordered image sequence. A second contribution of this work is a graph-based representation for 2D edges that allows the identification of the most structurally significant edges detected in an image. We integrate EdgeGraph3D in a multi-view stereo reconstruction pipeline and analyze the benefits provided by 3D edges to the accuracy of the recovered surfaces. We evaluate the effectiveness of our approach on multiple datasets from two different collections in the multi-view…
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