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A Survey of Voxel Interpolation Methods and an Evaluation of Their Impact on Volumetric Map-Based Visual Odometry
Univrses AB, Strängnäs, Sweden. (AASS MRO Lab)
Örebro University, School of Science and Technology. (AASS MRO Lab)ORCID iD: 0000-0002-6013-4874
Örebro University, School of Science and Technology. (AASS MRO Lab)ORCID iD: 0000-0003-0217-9326
2018 (English)In: Proceedings of the IEEE International Conference on Robotics and Automation (ICRA),, IEEE Computer Society, 2018, p. 6337-6343Conference paper, Published paper (Refereed)
Abstract [en]

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.

Place, publisher, year, edition, pages
IEEE Computer Society, 2018. p. 6337-6343
Keywords [en]
Voxels, Compression, Interpolation, TSDF, Visual Odometry
National Category
Robotics Computer Systems
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:oru:diva-67850ISI: 000446394504116OAI: oai:DiVA.org:oru-67850DiVA, id: diva2:1232362
Conference
IEEE International Conference on Robotics and Automation (ICRA), Brisbane, Australia, May 21-25, 2018
Projects
H2020 ILIADH2020 Roblog
Funder
EU, Horizon 2020, 732737Available from: 2018-07-11 Created: 2018-07-11 Last updated: 2018-10-22Bibliographically approved

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A Survey of Voxel Interpolation Methods and an Evaluation of Their Impact on Volumetric Map-Based Visual Odometry(719 kB)48 downloads
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Stoyanov, TodorLilienthal, Achim J.

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CiteExportLink to record
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