Dense Feature Matching for Structure from Motion


Simon Seibt1, Bartosz von Rymon Lipinski1, Thomas Chang1 and Marc Erich Latoschik2

1 Game Tech Lab, Nuremberg Institute of Technology
2 Human-Computer Interaction Group, University of Wuerzburgy

DFM4SfM result of the scene "Church" (Tanks and Temples dataset [1])


Structure from motion (SfM) is a fundamental task in computer vision and allows recovering the 3D structure of a stationary scene from an image set. Finding robust and accurate feature matches plays a crucial role in the early stages of SfM. So in this work, we propose a novel method for computing image correspondences based on dense feature matching (DFM) using homographic decomposition: The underlying pipeline provides refinement of existing matches through iterative rematching, detection of occlusions and extrapolation of additional matches in critical image areas between image pairs. Our main contributions are improvements of DFM specifically for SfM, resulting in global refinement and global extrapolation of image correspondences between related views. Furthermore, we propose an iterative version of the Delaunay-triangulation-based outlier detection algorithm for robust processing of repeated image patterns. Through experiments, we demonstrate that the proposed method significantly improves the reconstruction accuracy.


Pipeline Overview

UML activity diagram of the DFM4SfM pipeline, integrated into a SfM pipeline

Dense Feature Matching based on Homographic Decomposition

Global Refinement: Extension of positional refinement to a multi-view approach

Global Extrapolation: Mutual extrapolation of feature matches by considering multiple adjacent views

Visual Results

Comparison of the built-in feature matching approaches in COLMAP [2] and OpenMVG [3] with our DFM4SfM approach. A fixed ”test keypoint set” was initially detected.

Scene: Castle (DMVS dataset [4])

Scene: Facade (ETH3D dataset [5])

Scene: Terrains (ETH3D dataset [5])

Scene: Courtyard (ETH3D dataset [5])


author = {Seibt, Simon and Von Rymon Lipinski, Bartosz and Chang, Thomas and Latoschik, Marc Erich},
title = {DFM4SfM - Dense Feature Matching for Structure from Motion},
booktitle = {IEEE International Conference on Image Processing Workshops},
year = {2023},


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