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
[41]   An SE(3) invariant description for 3D face recognition [J].
Jribi, Majdi ;
Rihani, Amal ;
Ben Khlifa, Ameni ;
Ghorbel, Faouzi .
IMAGE AND VISION COMPUTING, 2019, 89 :106-119
[42]   Microstructural evolution in 3D: An existence result [J].
Kinderlehrer, David ;
Yun, KiHyun .
NONLINEAR ANALYSIS-THEORY METHODS & APPLICATIONS, 2025, 258
[43]   Rectilinear Path Following in 3D Space [J].
Hota, Sikha ;
Ghose, Debasish .
TRENDS IN INTELLIGENT ROBOTICS, 2010, 103 :210-217
[44]   Visual Attention for Rendered 3D Shapes [J].
Lavoue, Guillaume ;
Cordier, Frederic ;
Seo, Hyewon ;
Larabi, Mohamed-Chaker .
COMPUTER GRAPHICS FORUM, 2018, 37 (02) :191-203
[45]   Representational image generation for 3D objects [J].
Serin, Ekrem ;
Sumengen, Selcuk ;
Balcisoy, Selim .
VISUAL COMPUTER, 2013, 29 (6-8) :675-684
[46]   Viewing 3D MRI data in perspective [J].
Liu, HY ;
Chin, CL .
MATHEMATICAL MODELING, ESTIMATION, AND IMAGING, 2000, 4121 :202-207
[47]   3D Printing: Print the Future of Ophthalmology [J].
Huang, Wenbin ;
Zhang, Xiulan .
INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE, 2014, 55 (08) :5380-5381
[48]   3D fascicle orientations in triceps surae [J].
Rana, Manku ;
Hamarneh, Ghassan ;
Wakeling, James M. .
JOURNAL OF APPLIED PHYSIOLOGY, 2013, 115 (01) :116-125
[49]   Representational image generation for 3D objects [J].
Ekrem Serin ;
Selcuk Sumengen ;
Selim Balcisoy .
The Visual Computer, 2013, 29 :675-684
[50]   Visuohaptic Discrimination of 3D Gross Shape [J].
Kim, Kwangtaek ;
Barni, Mauro ;
Prattichizzo, Domenico ;
Tan, Hong Z. .
SEEING AND PERCEIVING, 2012, 25 (3-4) :351-364