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Authors: Ryo Hachiuma ; Yuko Ozasa and Hideo Saito

Affiliation: Keio University, Japan

Keyword(s): Superquadrics, 3D Shape Primitives, Primitive Shape Recognition, Large Margin Nearest Neighbor.

Abstract: It is known that humans recognize objects using combinations and positional relations of primitive shapes. The first step of such recognition is to recognize 3D primitive shapes. In this paper, we propose a method for primitive shape recognition using superquadric parameters with a metric learning method, large margin nearest neighbor (LMNN). Superquadrics can represent various types of primitive shapes using a single equation with few parameters. These parameters are used as the feature vector of classification. The real objects of primitive shapes are used in our experiment, and the results show the effectiveness of using LMNN for recognition based on superquadrics. Compared to the previous methods, which used k-nearest neighbors (76.5%) and Support Vector Machines (73.5%), our LMNN method has the best performance (79.5%).

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Paper citation in several formats:
Hachiuma, R.; Ozasa, Y. and Saito, H. (2017). Primitive Shape Recognition via Superquadric Representation using Large Margin Nearest Neighbor Classifier. In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017) - Volume 5: VISAPP; ISBN 978-989-758-226-4; ISSN 2184-4321, SciTePress, pages 325-332. DOI: 10.5220/0006153203250332

@conference{visapp17,
author={Ryo Hachiuma. and Yuko Ozasa. and Hideo Saito.},
title={Primitive Shape Recognition via Superquadric Representation using Large Margin Nearest Neighbor Classifier},
booktitle={Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017) - Volume 5: VISAPP},
year={2017},
pages={325-332},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006153203250332},
isbn={978-989-758-226-4},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017) - Volume 5: VISAPP
TI - Primitive Shape Recognition via Superquadric Representation using Large Margin Nearest Neighbor Classifier
SN - 978-989-758-226-4
IS - 2184-4321
AU - Hachiuma, R.
AU - Ozasa, Y.
AU - Saito, H.
PY - 2017
SP - 325
EP - 332
DO - 10.5220/0006153203250332
PB - SciTePress