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Title: Truncated octree and its applications
Authors: Koh, Naimin
Jayaraman, Pradeep Kumar
Zheng, Jianmin
Keywords: Engineering::Computer science and engineering
Issue Date: 2022
Source: Koh, N., Jayaraman, P. K. & Zheng, J. (2022). Truncated octree and its applications. Visual Computer, 38(4), 1167-1179.
Project: NRF2015VSG-AA3DCM001-018
MoE 2017-T2-1-076
Journal: Visual Computer
Abstract: Octree is a hierarchical data structure with many applications, especially in encoding unstructured point clouds. The depth of an octree is dependent of the scale of the input data and the desired resolution of the smallest voxels in the leaf nodes as well. Thus, it often requires a deep octree to maintain low level of geometric errors for large-scale sparse point clouds, which leads to high memory requirement and low access speed. This paper presents a new structure called truncated octree or T-Octree that truncates the octree by adaptively pruning the top hierarchy and represents the deep octree by a set of shallow sub-octrees. The structure is further extended to support random access of nodes and out-of-core streaming of large data sets. We also propose a variable length addressing scheme to adaptively choose the length of an octree’s node address based on the truncation level. As a result, T-Octree provides highly efficient query performance and can save storage without losing the original structure for sparse or clustered models and scenes. We demonstrate the efficacy and efficiency of the new structure on point cloud compression and scene query tasks for sparse or clustered data.
ISSN: 0178-2789
DOI: 10.1007/s00371-021-02130-5
Schools: School of Computer Science and Engineering 
Organisations: Autodesk Inc., Singapore
Rights: © 2021 The Authors, under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:SCSE Journal Articles

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