A Survey of Voxel Interpolation Methods and an Evaluation of Their Impact on Volumetric Map-Based Visual Odometry
Daniel Ricão Canelhas, Todor Stoyanov, and Achim J. Lilienthal
Proceedings of the International Conference on Robotics and Automation (ICRA) 2018
Abstract
Voxel volumes are simple to implement and lend themselves to many of the tools and algorithms available for 2D images. However, the additional dimension of voxels may be costly to manage in memory when mapping large spaces at high resolutions. While lowering the resolution and using interpolation is common work-around, in the literature we often find that authors either use trilinear interpolation or nearest neighbors and rarely any of the intermediate options. This paper presents a survey of geometric interpolation methods for voxel-based map representations. In particular we study the truncated signed distance field (TSDF) and the impact of using fewer than 8 samples to perform interpolation within a depth-camera pose tracking and mapping scenario. We find that lowering the number of samples fetched to perform the interpolation results in performance similar to the commonly used trilinear interpolation method, but leads to higher framerates. We also report that lower bit-depth generally leads to performance degradation, though not as much as may be expected, with voxels containing as few as 3 bits sometimes resulting in adequate estimation of camera trajectories.
@inproceedings{Cane18,
author = {D. R. Canelhas and T. Stoyanov and A. J. Lilienthal},
booktitle = {Proc. of the IEEE Int. Conf. on Robotics and Automation},
institution = {\"Orebro University, School of Science and Technology},
title = {A Survey of Voxel Interpolation Methods and an Evaluation of Their Impact on Volumetric Map-Based Visual Odometry},
year = {2018}
}