2015 RSS RSS 2015

Chisel: Real Time Large Scale 3D Reconstruction Onboard a Mobile Device using Spatially Hashed Signed Distance Fields

Abstract

We describe Chisel : a system for real-time house-scale (300 square meter or more) dense 3D reconstruction onboard a Google Tango mobile device by using a dynamic spatially-hashed truncated signed distance field for mapping, and visual-inertial odometry for localization. By aggressively culling parts of the scene that do not contain surfaces, we avoid needless computation and wasted memory. Even under very noisy conditions, we produce high-quality reconstructions through the use of space carving. We are able to reconstruct and render very large scenes at a resolution of 2-3 cm in real time on a mobile device without the use of GPU computing. The user is able to view and interact with the reconstruction in real-time through an intuitive interface. We provide both qualitative and quantitative results on publicly available RGB-D datasets, and on datasets collected in real-time from two devices.

🌉 Interdisciplinary Bridge — Artificial Intelligence and Computer Vision
🧭 Keyword Pioneer — signed distance field
🐣 Hot Topic Early Bird — signed distance field
🐝 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