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Paper Abstract and Keywords
Presentation 2019-12-20 16:20
A Preliminary Study on BTF Image Database Generation using Deep Learning
Naoki Tada, Keita Hirai (Chiba Univ.) IMQ2019-10
Abstract (in Japanese) (See Japanese page) 
(in English) A method using Bidirectional Texture Function (BTF) is one of the methods to reproduce a realistic image in Computer Graphics (CG). The BTF-based method is a method of mapping texture images according to the scene illumination and viewpoint position to the object to be reproduced and can reproduce a realistic appearance with simple and high-speed processing. However, we generally have to measure and retain a large amount of texture data in advance to reproduce CG based on BTF. In this paper, to solve the problems related to enormous measurement data for BTF reproduction, we generated BTF image data which includes various azimuth condition of illumination from a single texture image using deep learning (U-Net). Also, we evaluated the restored image by objective image quality index and confirmed that the reproducibility was high.
Keywords BTF, U-Net, Convolutional neural network, texture mapping, Computer Graphics,Deep Learning
Keyword (in Japanese) (See Japanese page) 
(in English) BTF / U-Net / Convolutional neural network / texture mapping / Deep Learning / Computer Graphics / /  
Reference Info. IEICE Tech. Rep., vol. 119, no. 349, IMQ2019-10, pp. 3-8, Dec. 2019.
Paper # IMQ2019-10 
Date of Issue 2019-12-13 (IMQ) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380
Copyright
and
reproduction
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. (No. 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF IMQ2019-10

Conference Information
Committee IMQ  
Conference Date 2019-12-20 - 2019-12-20 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
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Paper Information
Registration To IMQ 
Conference Code 2019-12-IMQ 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Preliminary Study on BTF Image Database Generation using Deep Learning 
Sub Title (in English)  
Keyword(1) BTF  
Keyword(2) U-Net  
Keyword(3) Convolutional neural network  
Keyword(4) texture mapping  
Keyword(5) Deep Learning  
Keyword(6) Computer Graphics  
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Keyword(8)  
1st Author's Name Naoki Tada  
1st Author's Affiliation Chiba University (Chiba Univ.)
2nd Author's Name Keita Hirai  
2nd Author's Affiliation Chiba University (Chiba Univ.)
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Speaker
Date Time 2019-12-20 16:20:00 
Presentation Time 25 
Registration for IMQ 
Paper # IEICE-IMQ2019-10 
Volume (vol) IEICE-119 
Number (no) no.349 
Page pp.3-8 
#Pages IEICE-6 
Date of Issue IEICE-IMQ-2019-12-13 


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