Universität Bonn: Autonomous Intelligent Systems Group   Comouter Science Institute VI: Autonomous Intelligent Systems

Malte Splietker and Sven Behnke:
Directional TSDF: Modeling Surface Orientation for Coherent Meshes
In Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Macau, China, November 2019.

Abstract

Real-time 3D reconstruction from RGB-D sensor data plays an important role in many robotic applications, such as object modeling and mapping. The popular method of fusing depth information into a truncated signed distance function (TSDF) and applying the marching cubes algorithm for mesh extraction has severe issues with thin structures: not only does it lead to loss of accuracy, but it can generate completely wrong surfaces. To address this, we propose the directional TSDF – a novel representation that stores opposite surfaces separate from each other. The marching cubes algorithm is modified accordingly to retrieve a coherent mesh representation. We further increase the accuracy by using surface gradient-based ray casting for fusing new measurements. We show that our method outperforms state-of-the-art TSDF reconstruction algorithms in mesh accuracy.

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Source Code

The original source code used for this paper can be found [here].
We since moved to a different code base for our follow-up work on tracking the directional TSDF [project page | code].

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