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Paper Abstract and Keywords
Presentation 2017-03-21 14:10
Three-dimensional shape retrieval based in voxel representation using LSTM and CNN
Ryo Miyagi, Masaki Aono (TUT) BioX2016-67 PRMU2016-230
Abstract (in Japanese) (See Japanese page) 
(in English) In recent years, with the spread of 3D scanners, VR headsets, etc., there is an increasing demand for recognition and retrieval for 3D contents. Furthermore, by applying deep learning to 3-dimensional objects, research on shape classification, shape search and the like are actively conducted. In this paper, we represent our model with binary voxels and propose a new method for searching similar 3D shape models using deep learning. Specifically, we employ a Convolutional Neural Network (CNN) to represent a 2D slice extracting from 3D binary voxels, and a Long Short-Term Memory (LSTM) to represent 2D slices as time-series connected features showing a given 3D shape. As a result of the experiment, we could improve the performance of our method against a baseline method which is based on 3DCNN.
Keyword (in Japanese) (See Japanese page) 
(in English) Deep Learning / 3D / LSTM / CNN / Shape Retrieval / Binary Voxel / /  
Reference Info. IEICE Tech. Rep., vol. 116, no. 528, PRMU2016-230, pp. 203-208, March 2017.
Paper # PRMU2016-230 
Date of Issue 2017-03-13 (BioX, PRMU) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF BioX2016-67 PRMU2016-230

Conference Information
Committee PRMU BioX  
Conference Date 2017-03-20 - 2017-03-21 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
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Paper Information
Registration To PRMU 
Conference Code 2017-03-PRMU-BioX 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Three-dimensional shape retrieval based in voxel representation using LSTM and CNN 
Sub Title (in English)  
Keyword(1) Deep Learning  
Keyword(2) 3D  
Keyword(3) LSTM  
Keyword(4) CNN  
Keyword(5) Shape Retrieval  
Keyword(6) Binary Voxel  
1st Author's Name Ryo Miyagi  
1st Author's Affiliation Toyohashi University of Technology (TUT)
2nd Author's Name Masaki Aono  
2nd Author's Affiliation Toyohashi University of Technology (TUT)
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Date Time 2017-03-21 14:10:00 
Presentation Time 25 
Registration for PRMU 
Paper # IEICE-BioX2016-67,IEICE-PRMU2016-230 
Volume (vol) IEICE-116 
Number (no) no.527(BioX), no.528(PRMU) 
Page pp.203-208 
#Pages IEICE-6 
Date of Issue IEICE-BioX-2017-03-13,IEICE-PRMU-2017-03-13 

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