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Authors: Viktor Seib ; Nick Theisen and Dietrich Paulus

Affiliation: Active Vision Group (AGAS), University of Koblenz-Landau, Universitätsstr. 1, 56070 Koblenz and Germany

Keyword(s): Shape Classification, Global Verification, Mobile Robotics, Implicit Shape Models, Point Clouds, Codebooks.

Related Ontology Subjects/Areas/Topics: Applications ; Pattern Recognition ; Robotics ; Software Engineering

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.

CC BY-NC-ND 4.0

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Paper citation in several formats:
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; ISSN 2184-4321, SciTePress, pages 257-264. DOI: 10.5220/0007312402570264

@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},
issn={2184-4321},
}

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
IS - 2184-4321
AU - Seib, V.
AU - Theisen, N.
AU - Paulus, D.
PY - 2019
SP - 257
EP - 264
DO - 10.5220/0007312402570264
PB - SciTePress

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