Robust and Practical Depth Map Fusion for Time-of-Flight Cameras

Markus Ylimäki1, Juho Kannala2, Janne Heikkilä1
1Center for Machine Vision Research
University of Oulu, Finland

2Department of Computer Science
Aalto University, Espoo, Finland

The paper was published in Scandinavian Conference on Image Analysis in June 2017.


Fusion of overlapping depth maps is an important part in many 3D reconstruction pipelines. Ideally fusion produces an accurate and nonredundant point cloud robustly even from noisy and partially poorly registered depth maps. In this paper, we improve an existing fusion algorithm towards a more ideal solution. Our method builds a nonredundant point cloud from a sequence of depth maps so that the new measurements are either added to the existing point cloud if they are in an area which is not yet covered or used to refine the existing points. The method is robust to outliers and erroneous depth measurements as well as small depth map registration errors due to inaccurate camera poses. The results show that the method overcomes its predecessor both in accuracy and robustness.



Markus Ylimäki