Boosting 3D Shape Classification with Global Verification and Redundancy-free Codebooks

Viktor Seib, Nick Theisen, Dietrich Paulus

2019

Abstract

We present a competitive approach for 3D data classification that is related to Implicit Shape Models and Naive-Bayes Nearest Neighbor algorithms. Based on this approach we investigate methods to reduce the amount of data stored in the extracted codebook with the goal to eliminate redundant and ambiguous feature descriptors. The codebook is significantly reduced in size and is combined with a novel global verification approach. We evaluate our algorithms on typical 3D data benchmarks and achieve competitive results despite the reduced codebook. The presented algorithm can be run efficiently on a mobile computer making it suitable for mobile robotics applications. The source code of the developed methods is made publicly available to contribute to point cloud processing, the Point Cloud Library (PCL) and 3D classification software in general.

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Paper Citation


in Harvard Style

Seib V., Theisen N. and Paulus D. (2019). Boosting 3D Shape Classification with Global Verification and Redundancy-free Codebooks. In Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 5: VISAPP; ISBN 978-989-758-354-4, SciTePress, pages 257-264. DOI: 10.5220/0007312402570264


in Bibtex Style

@conference{visapp19,
author={Viktor Seib and Nick Theisen and Dietrich Paulus},
title={Boosting 3D Shape Classification with Global Verification and Redundancy-free Codebooks},
booktitle={Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 5: VISAPP},
year={2019},
pages={257-264},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007312402570264},
isbn={978-989-758-354-4},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 5: VISAPP
TI - Boosting 3D Shape Classification with Global Verification and Redundancy-free Codebooks
SN - 978-989-758-354-4
AU - Seib V.
AU - Theisen N.
AU - Paulus D.
PY - 2019
SP - 257
EP - 264
DO - 10.5220/0007312402570264
PB - SciTePress