中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Data-Driven Shape Analysis and Processing.

文献类型:期刊论文

作者Kalogerakis, Evangelos; Xu, Kai; Kim, Vladimir G; Huang, Qixing
刊名COMPUTER GRAPHICS FORUM
出版日期2017
文献子类期刊论文
英文摘要Data-driven methods serve an increasingly important role in discovering geometric, structural and semantic relationships between shapes. In contrast to traditional approaches that process shapes in isolation of each other, data-driven methods aggregate information from 3D model collections to improve the analysis, modelling and editing of shapes. Data-driven methods are also able to learn computational models that reason about properties and relationships of shapes without relying on hard-coded rules or explicitly programmed instructions. Through reviewing the literature, we provide an overview of the main concepts and components of these methods, as well as discuss their application to classification, segmentation, matching, reconstruction, modelling and exploration, as well as scene analysis and synthesis. We conclude our report with ideas that can inspire future research in data-driven shape analysis and processing.
URL标识查看原文
语种英语
源URL[http://ir.siat.ac.cn:8080/handle/172644/12436]  
专题深圳先进技术研究院_数字所
作者单位COMPUTER GRAPHICS FORUM
推荐引用方式
GB/T 7714
Kalogerakis, Evangelos,Xu, Kai,Kim, Vladimir G,et al. Data-Driven Shape Analysis and Processing.[J]. COMPUTER GRAPHICS FORUM,2017.
APA Kalogerakis, Evangelos,Xu, Kai,Kim, Vladimir G,&Huang, Qixing.(2017).Data-Driven Shape Analysis and Processing..COMPUTER GRAPHICS FORUM.
MLA Kalogerakis, Evangelos,et al."Data-Driven Shape Analysis and Processing.".COMPUTER GRAPHICS FORUM (2017).

入库方式: OAI收割

来源:深圳先进技术研究院

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