2015 ICCV ICCV 2015

Towards Pointless Structure From Motion: 3D Reconstruction and Camera Parameters From General 3D Curves

Abstract

Modern structure from motion (SfM) remains dependent on point features to recover camera positions, meaning that reconstruction is severely hampered in low-texture environments, for example scanning a plain coffee cup on an uncluttered table. We show how 3D curves can be used to refine camera position estimation in challenging low-texture scenes. In contrast to previous work, we allow the curves to be partially observed in all images, meaning that for the first time, curve-based SfM can be demonstrated in realistic scenes. The algorithm is based on bundle adjustment, so needs an initial estimate, but even a poor estimate from a few point correspondences can be substantially improved by including curves, suggesting that this method would benefit many existing systems.

🧭 Keyword Pioneer — curve reconstruction
🐣 Hot Topic Early Bird — camera pose estimation
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio