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Authors: Jens Garstka and Gabriele Peters

Affiliation: Faculty of Mathematics and Computer Science and University of Hagen, Germany

Keyword(s): Local 3-D Feature Descriptors, Performance Evaluation, Object Classification.

Related Ontology Subjects/Areas/Topics: Informatics in Control, Automation and Robotics ; Robotics and Automation ; Vision, Recognition and Reconstruction

Abstract: This paper investigates existing methods for local 3-D feature description with special regards to their suitability for object classification based on 3-D point cloud data. We choose five approved descriptors, namely Spin Images, Point Feature Histogram, Fast Point Feature Histogram, Signature of Histograms of Orientations, and Unique Shape Context and evaluate them with a commonly used classification pipeline on a large scale 3-D object dataset comprising more than 200000 different point clouds. Of particular interest are the details of the choice of all parameters associated with the classification pipeline. The point clouds are classified by using support vector machines. Fast Point Feature Histogram proves to be the best descriptor for the method of object classification used in this evaluation.

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Paper citation in several formats:
Garstka, J. and Peters, G. (2016). Evaluation of Local 3-D Point Cloud Descriptors in Terms of Suitability for Object Classification. In Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO; ISBN 978-989-758-198-4; ISSN 2184-2809, SciTePress, pages 540-547. DOI: 10.5220/0006011505400547

@conference{icinco16,
author={Jens Garstka. and Gabriele Peters.},
title={Evaluation of Local 3-D Point Cloud Descriptors in Terms of Suitability for Object Classification},
booktitle={Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO},
year={2016},
pages={540-547},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006011505400547},
isbn={978-989-758-198-4},
issn={2184-2809},
}

TY - CONF

JO - Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO
TI - Evaluation of Local 3-D Point Cloud Descriptors in Terms of Suitability for Object Classification
SN - 978-989-758-198-4
IS - 2184-2809
AU - Garstka, J.
AU - Peters, G.
PY - 2016
SP - 540
EP - 547
DO - 10.5220/0006011505400547
PB - SciTePress

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