In accordance with regulations and requirements, the editorial department's website domain has been changed to arocmag.cn. The original domain (arocmag.com) will be discontinued after Dec. 31st, 2024.
Technology of Graphic & Image
|
605-610

Semantic feature lines extraction on mesh model based on saliency analysis

Guo Yihui
Zhong Xueling
Lu Jiyuan
Huang Chenghui
School of Internet Finance & Information Engineering, Guangdong University of Finance, Guangzhou 510020, China

Abstract

The available mesh feature lines extraction methods based on the differential geometry properties cannot describe the global semantic characteristics well. To solve the problem, this paper proposed a method of extracting semantic feature lines of mesh model based on saliency analysis and human attention mechanism. Firstly, the method used the spectral theory to construct a smooth three-dimensional datum of the mesh model, obtained the salient vertices of the mesh. And then the method used the directional attributes of the discrete Laplacian-Beltrami operators to construct the mesh semantic feature areas, extracted and optimized the skeletons of the feature regions, and obtained the semantic feature lines of the model finally. The method hasn't need to measure the local differential properties of the mesh at all, and the experimental results show that the method can accurately extract the semantic feature lines, which can describe the global meaningful features of the model well.

Foundation Support

国家自然科学基金资助项目(71501051,61872394,61772149)
广东省普通高校人文社会科学研究重点项目(2018WZDXM032)
广东省普通高校科研平台和科研创新项目(2020KTSCX085)
广东省自然科学基金资助项目(2017A050501042)
广州市科技计划项目(202002030473)
广东省基础与应用基础研究基金资助项目(2019A1515011953)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2019.10.0641
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 2
Section: Technology of Graphic & Image
Pages: 605-610
Serial Number: 1001-3695(2021)02-056-0605-06

Publish History

[2021-02-05] Printed Article

Cite This Article

郭艺辉, 钟雪灵, 陆寄远, 等. 基于显著性分析的网格模型语义特征线提取 [J]. 计算机应用研究, 2021, 38 (2): 605-610. (Guo Yihui, Zhong Xueling, Lu Jiyuan, et al. Semantic feature lines extraction on mesh model based on saliency analysis [J]. Application Research of Computers, 2021, 38 (2): 605-610. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.


Indexed & Evaluation

  • The Second National Periodical Award 100 Key Journals
  • Double Effect Journal of China Journal Formation
  • the Core Journal of China (Peking University 2023 Edition)
  • the Core Journal for Science
  • Chinese Science Citation Database (CSCD) Source Journals
  • RCCSE Chinese Core Academic Journals
  • Journal of China Computer Federation
  • 2020-2022 The World Journal Clout Index (WJCI) Report of Scientific and Technological Periodicals
  • Full-text Source Journal of China Science and Technology Periodicals Database
  • Source Journal of China Academic Journals Comprehensive Evaluation Database
  • Source Journals of China Academic Journals (CD-ROM Version), China Journal Network
  • 2017-2019 China Outstanding Academic Journals with International Influence (Natural Science and Engineering Technology)
  • Source Journal of Top Academic Papers (F5000) Program of China's Excellent Science and Technology Journals
  • Source Journal of China Engineering Technology Electronic Information Network and Electronic Technology Literature Database
  • Source Journal of British Science Digest (INSPEC)
  • Japan Science and Technology Agency (JST) Source Journal
  • Russian Journal of Abstracts (AJ, VINITI) Source Journals
  • Full-text Journal of EBSCO, USA
  • Cambridge Scientific Abstracts (Natural Sciences) (CSA(NS)) core journals
  • Poland Copernicus Index (IC)
  • Ulrichsweb (USA)