loading
Documents

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Ryoma Yataka and Kazuhiro Fukui

Affiliation: University of Tsukuba, Japan

ISBN: 978-989-758-222-6

ISSN: 2184-4313

Keyword(s): Three-dimensional Object Recognition, Subspace Representation, Canonical Angles, Grassmann Manifold, Mutual Subspace Method.

Related Ontology Subjects/Areas/Topics: Applications ; Classification ; Embedding and Manifold Learning ; Object Recognition ; Pattern Recognition ; Software Engineering ; Theory and Methods

Abstract: In this paper, we propose a method for recognizing three-dimensional (3D) objects using multi-view depth images. To derive the essential 3D shape information extracted from these images for stable and accurate 3D object recognition, we need to consider how to integrate partial shapes of a 3D object. To address this issue, we introduce two ideas. The first idea is to represent a partial shape of the 3D object by a three-dimensional subspace in a high-dimensional vector space. The second idea is to represent a set of the shape subspaces as a subspace on a Grassmann manifold, which reflects the 3D shape of the object more completely. Further, we measure the similarity between two subspaces on the Grassmann manifold by using the canonical angles between them. This measurement enables us to construct a more stable and accurate method based on richer information about the 3D shape. We refer to this method based on subspaces on a Grassmann manifold as the Grassmann mutual subspace method (GM SM). To further enhance the performance of the GMSM, we equip it with powerful feature-extraction capabilities. The validity of the proposed method is demonstrated through experimental comparisons with several conventional methods on a hand-depth image dataset. (More)

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 35.168.111.204

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Yataka, R. and Fukui, K. (2017). Three-dimensional Object Recognition via Subspace Representation on a Grassmann Manifold.In Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-222-6, ISSN 2184-4313, pages 208-216. DOI: 10.5220/0006204702080216

@conference{icpram17,
author={Ryoma Yataka. and Kazuhiro Fukui.},
title={Three-dimensional Object Recognition via Subspace Representation on a Grassmann Manifold},
booktitle={Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2017},
pages={208-216},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006204702080216},
isbn={978-989-758-222-6},
}

TY - CONF

JO - Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Three-dimensional Object Recognition via Subspace Representation on a Grassmann Manifold
SN - 978-989-758-222-6
AU - Yataka, R.
AU - Fukui, K.
PY - 2017
SP - 208
EP - 216
DO - 10.5220/0006204702080216

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.