Simulating Structure-from-Motion

TL;DR

This paper develops and evaluates a synthetic scene-based Structure-from-Motion pipeline, comparing reconstructions to ground truth and exploring methods to improve camera pose accuracy.

Contribution

It introduces a synthetic scene approach for SfM and investigates the impact of ground truth data injection on pose estimation accuracy.

Findings

Reconstructed camera poses are compared with ground truth data.

Injecting ground truth locations reduces camera pose estimation errors.

Multiple SfM reconstructions demonstrate the method's effectiveness.

Abstract

The implementation of a Structure-from-Motion (SfM) pipeline from a synthetically generated scene as well as the investigation of the faithfulness of diverse reconstructions is the subject of this project. A series of different SfM reconstructions are implemented and their camera pose estimations are being contrasted with their respective ground truth locations. Finally, injection of ground truth location data into the rendered images in order to reduce the estimation error of the camera poses is studied as well.