The effectiveness of random selection for IGA-based texture search

K. Ishibashi
{"title":"The effectiveness of random selection for IGA-based texture search","authors":"K. Ishibashi","doi":"10.1109/SNPD.2017.8022793","DOIUrl":null,"url":null,"abstract":"This paper provides a novel texture search method for texture images. Creating a computer graphics (CG) is a popular task in many media creations. However, CG creators require their abundant time and effort. In addition, it is difficult for non-professional creators to make a 3D CG scene. This is because that they have to choose appropriate colors, textures, and lighting patterns in addition to 3D CG modeling. To reduce creators' work time and effort, some prior studies have tried to support for 3D CG creations by procedural modeling, texture synthesis, or automatic parameter setting technique. However, there are no supporting systems for choosing textures. Thus, this study addresses the problem. The proposed method enables to choose an appropriate texture image easily and quickly. The method uses an interactive genetic algorithm (IGA) with random selection (RS) system. This paper describes a framework of the proposed method using IGA with RS.","PeriodicalId":186094,"journal":{"name":"2017 18th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 18th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SNPD.2017.8022793","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

This paper provides a novel texture search method for texture images. Creating a computer graphics (CG) is a popular task in many media creations. However, CG creators require their abundant time and effort. In addition, it is difficult for non-professional creators to make a 3D CG scene. This is because that they have to choose appropriate colors, textures, and lighting patterns in addition to 3D CG modeling. To reduce creators' work time and effort, some prior studies have tried to support for 3D CG creations by procedural modeling, texture synthesis, or automatic parameter setting technique. However, there are no supporting systems for choosing textures. Thus, this study addresses the problem. The proposed method enables to choose an appropriate texture image easily and quickly. The method uses an interactive genetic algorithm (IGA) with random selection (RS) system. This paper describes a framework of the proposed method using IGA with RS.
基于iga的随机选择纹理搜索的有效性
本文提出了一种新的纹理图像搜索方法。在许多媒体创作中,创建计算机图形(CG)是一项流行的任务。然而,CG创作者需要他们大量的时间和精力。此外,对于非专业创作者来说,制作3D CG场景是很困难的。这是因为除了3D CG建模之外,他们还必须选择合适的颜色,纹理和照明模式。为了减少创作者的工作时间和精力,一些先前的研究试图通过程序建模、纹理合成或自动参数设置技术来支持3D CG创作。然而,没有支持选择纹理的系统。因此,本研究解决了这个问题。该方法能够方便、快速地选择合适的纹理图像。该方法采用交互式遗传算法(IGA)和随机选择(RS)系统。本文描述了采用IGA和RS的方法的框架。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信