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Paper Abstract and Keywords
Presentation 2022-11-04 16:30
Fitness Evaluation Based on 3D Model Generation System by Fractal Model and Genetic Algorithm
Kaito Watanabe, Naoto Hoshikawa (NIT, Oyama College), Hirotaka Nakayama (NAOJ), Tomoyoshi Ito, Atushi Shiraki (Chiba Univ) KBSE2022-36 SC2022-31
Abstract (in Japanese) (See Japanese page) 
(in English) In recent years, the 3DCG-related industry has grown rapidly, and the demand for 3DCG content creation has increased, but 3DCG production requires specialized skills and a great deal of time. In particular, the background data is large-scale, and it is a problem that many human resources cannot be allocated. Therefore, in this research, we propose an AI that automates the work involved in creating large-scale 3D models. The proposed system consists of 3D model generation, optimization of parameters for generation, and fitness evaluation. In this research, we propose a method using AKAZE and VGG19 for fitness evaluation and discuss the optimization behavior through experiments.
Keyword (in Japanese) (See Japanese page) 
(in English) Fractal Model / Genetic Algorithm / 3D-Modeling / 3DCG / AKAZE / VGG19 / /  
Reference Info. IEICE Tech. Rep., vol. 122, no. 239, SC2022-31, pp. 31-36, Nov. 2022.
Paper # SC2022-31 
Date of Issue 2022-10-28 (KBSE, SC) 
ISSN 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 KBSE2022-36 SC2022-31

Conference Information
Committee KBSE SC  
Conference Date 2022-11-04 - 2022-11-05 
Place (in Japanese) (See Japanese page) 
Place (in English)  
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Topics (in English)  
Paper Information
Registration To SC 
Conference Code 2022-11-KBSE-SC 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Fitness Evaluation Based on 3D Model Generation System by Fractal Model and Genetic Algorithm 
Sub Title (in English)  
Keyword(1) Fractal Model  
Keyword(2) Genetic Algorithm  
Keyword(3) 3D-Modeling  
Keyword(4) 3DCG  
Keyword(5) AKAZE  
Keyword(6) VGG19  
1st Author's Name Kaito Watanabe  
1st Author's Affiliation National Institute of Technology, Oyama College (NIT, Oyama College)
2nd Author's Name Naoto Hoshikawa  
2nd Author's Affiliation National Institute of Technology, Oyama College (NIT, Oyama College)
3rd Author's Name Hirotaka Nakayama  
3rd Author's Affiliation National Astronomical Observatory of Japan (NAOJ)
4th Author's Name Tomoyoshi Ito  
4th Author's Affiliation Chiba University (Chiba Univ)
5th Author's Name Atushi Shiraki  
5th Author's Affiliation Chiba University (Chiba Univ)
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Speaker Author-1 
Date Time 2022-11-04 16:30:00 
Presentation Time 45 minutes 
Registration for SC 
Paper # KBSE2022-36, SC2022-31 
Volume (vol) vol.122 
Number (no) no.238(KBSE), no.239(SC) 
Page pp.31-36 
Date of Issue 2022-10-28 (KBSE, SC) 

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