Overview of 3D Scene Viewpoints evaluation method

被引:0
作者
Zhang Y. [1 ]
Fei G. [1 ]
机构
[1] School of Animation and Digital Arts, Communication University of China, Beijing
来源
Virtual Reality and Intelligent Hardware | 2019年 / 1卷 / 04期
关键词
Curvature; Mesh saliency; Three-dimensional scene; View point; Visual perception;
D O I
10.1016/j.vrih.2019.01.001
中图分类号
学科分类号
摘要
The research on 3D scene viewpoints has been a frontier problem in computer graphics and virtual reality technology. In a pioneering study, it had been extensively used in virtual scene understanding, image-based modeling, and visualization computing. With the development of computer graphics and the human-computer interaction, the viewpoint evaluation becomes more significant for the comprehensive understanding of complex scenes. The high-quality viewpoints could navigate observers to the region of interest, help subjects to seek the hidden relations of hierarchical structure, and improve the efficiency of virtual exploration. These studies later contributed to research such as robot vision, dynamic scene planning, virtual driving and artificial intelligence navigation.The introduction of visual perception had The introduction of visual perception had contributed to the inspiration of viewpoints research, and the combination with machine learning made significant progress in the viewpoints selection. The viewpoints research also has been significant in the optimization of global lighting, visualization calculation, 3D supervising rendering, and reconstruction of a virtual scene. Additionally, it has a huge potential in novel fields such as 3D model retrieval, virtual tactile analysis, human visual perception research, salient point calculation, ray tracing optimization, molecular visualization, and intelligent scene computing. © 2019 Beijing Zhongke Journal Publishing Co. Ltd
引用
收藏
页码:341 / 385
页数:44
相关论文
共 50 条
  • [21] A comprehensive overview of deep learning techniques for 3D point cloud classification and semantic segmentation
    Sarker, Sushmita
    Sarker, Prithul
    Stone, Gunner
    Gorman, Ryan
    Tavakkoli, Alireza
    Bebis, George
    Sattarvand, Javad
    MACHINE VISION AND APPLICATIONS, 2024, 35 (04)
  • [22] Local Projections Method and Curvature Approximation of 3D Polygonal Models
    Hulik, Rostislav
    Krsek, Premysl
    WSCG'2012, CONFERENCE PROCEEDINGS, PTS I & II, 2012, : 223 - 230
  • [23] A Watermarking Method for 3D Models Based on Feature Vertex Localization
    Liu, Jing
    Yang, Yam
    Ma, Douli
    Wang, Yinghui
    Pan, Zhigeng
    IEEE ACCESS, 2018, 6 : 56122 - 56134
  • [24] Novel 3D Mesh Quality Assessment Method Based on Curvature
    Lin, Yaoyao
    Yu, Mei
    Jiang, Gangyi
    Song, Yang
    Shao, Hua
    OPTOELECTRONIC IMAGING AND MULTIMEDIA TECHNOLOGY V, 2018, 10817
  • [25] Research on Method of 3D Models Viewpoint Control Based on VRML
    Pan Tong
    Li Xiao-jing
    Wang Hao-peng
    Liu Ting-ting
    MATERIALS PROCESSING AND MANUFACTURING III, PTS 1-4, 2013, 753-755 : 1283 - 1286
  • [26] A clustering-based method to estimate saliency in 3D animated meshes
    Bulbul, Abdullah
    Arpa, Sami
    Capin, Tolga
    COMPUTERS & GRAPHICS-UK, 2014, 43 : 11 - 20
  • [27] Damage detection of 3D structures using nearest neighbor search method
    Abasi, Ali
    Harsij, Vahid
    Soraghi, Ahmad
    EARTHQUAKE ENGINEERING AND ENGINEERING VIBRATION, 2021, 20 (03) : 705 - 725
  • [28] PRE-PROCESSING OF HOLOSCOPIC 3D IMAGE FOR AUTOSTEREOSCOPIC 3D DISPLAYS
    Swash, M. R.
    Aggoun, A.
    Abdulfatah, O.
    Li, B.
    Fernandez, J. C.
    Alazawi, E.
    Tsekleves, E.
    2013 INTERNATIONAL CONFERENCE ON 3D IMAGING (IC3D), 2013,
  • [29] A Perceptual Structural Degradation Metric for 3D Mesh Processing
    Shi, Zhenfeng
    Zhang, Chiping
    Niu, Xiamu
    PROCEEDINGS OF THE 2011 INTERNATIONAL CONFERENCE ON INFORMATICS, CYBERNETICS, AND COMPUTER ENGINEERING (ICCE2011), VOL 2: INFORMATION SYSTEMS AND COMPUTER ENGINEERING, 2011, 111 : 609 - +
  • [30] Visual detection of 3D mirror-symmetry and 3D rotational-symmetry
    Sawada, T.
    Farshchi, M.
    VISUAL COGNITION, 2022, 30 (08) : 546 - 563