Adaptive-resolution octree-based volumetric SLAM

被引：16

作者：

Vespa, Emanuele ^{[1
]}

Funk, Nils ^{[1
]}

Kelly, Paul H. J. ^{[1
]}

Leutenegger, Stefan ^{[1
]}

机构：

[1] Imperial Coll London, Dept Comp, London, England

来源：

2019 INTERNATIONAL CONFERENCE ON 3D VISION (3DV 2019) | 2019年

基金：

英国工程与自然科学研究理事会;

关键词：

D O I：

10.1109/3DV.2019.00077

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We introduce a novel volumetric SLAM pipeline for the integration and rendering of depth images at an adaptive level of detail. Our core contribution is a fusion algorithm which dynamically selects the appropriate integration scale based on the effective sensor resolution given the distance from the observed scene, addressing aliasing issues, reconstruction quality, and efficiency simultaneously. We implement our approach using an efficient octree structure which supports multi-resolution rendering allowing for online frame-to-model alignment. Our qualitative and quantitative experiments demonstrate significantly improved reconstruction quality and up to six-fold execution time speed-ups compared to single resolution grids.

引用

页码：654 / 662

页数：9

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