Combining CSG modeling with soft blending using Lipschitz-based implicit surfaces

被引:4
|
作者
Dekkers, D [1 ]
van Overveld, K [1 ]
Golsteijn, R [1 ]
机构
[1] Eindhoven Univ Technol, NL-5600 MB Eindhoven, Netherlands
来源
VISUAL COMPUTER | 2004年 / 20卷 / 06期
关键词
implicit surface; smooth blending; Lipschitz condition;
D O I
10.1007/s00371-002-0198-3
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
In this paper a general method is given for combining CSG modeling with soft blending using implicit surfaces. A class of various blending functions sharing some desirable properties like differentiability and intuitive blend control are given. The functions defining the CSG objects satisfy the Lipschitz condition that gives the possibility of fast root finding but can also prove useful in the field of collision detection and adaptive triangulation.
引用
收藏
页码:380 / 391
页数:12
相关论文
共 50 条
  • [41] Active Perception and Modeling of Deformable Surfaces using Gaussian Processes and Position-based Dynamics
    Caccamo, Sergio
    Guler, Puren
    Kjellstrom, Hedvig
    Kragic, Danica
    2016 IEEE-RAS 16TH INTERNATIONAL CONFERENCE ON HUMANOID ROBOTS (HUMANOIDS), 2016, : 530 - 537
  • [42] A new user-friendly sketch-based modeling method using convolution surfaces
    Ramos, Marcos, Jr.
    Teixeira, Leandro
    Martins, Vitor
    Montenegro, Anselmo
    Trevisan, Daniela G.
    Vasconcelos, Cristina Nader
    2016 18TH SYMPOSIUM ON VIRTUAL AND AUGMENTED REALITY (SVR 2016), 2016, : 100 - 108
  • [43] Modeling of macrosegregation benchmarks using a stabilized finite element algorithm based on a semi-implicit pressure correction scheme
    Chen, Kangxin
    Shen, Houfa
    INTERNATIONAL JOURNAL OF NUMERICAL METHODS FOR HEAT & FLUID FLOW, 2020, 30 (02) : 918 - 933
  • [44] Development of a semi-implicit fluid modeling code using finite-volume method based on Cartesian grids
    Smith, Matthew R.
    Hung, Chieh-Tsan
    Lin, Kun-Mo
    Wu, Jong-Shinn
    Yu, Jen-Perng
    COMPUTER PHYSICS COMMUNICATIONS, 2011, 182 (01) : 170 - 172
  • [45] Sensitivity Analysis of ZnO NWs Based Soft Capacitive Pressure Sensors using Finite Element Modeling
    Mishra, Shashank
    Baghini, Mahdieh Shojaei
    Shakthivel, Dhayalan
    Rai, Beena
    Dahiya, Ravinder
    2022 IEEE INTERNATIONAL CONFERENCE ON FLEXIBLE AND PRINTABLE SENSORS AND SYSTEMS (IEEE FLEPS 2022), 2022,
  • [46] Design and Modeling of a New Biomimetic Soft Robotic Jellyfish Using IPMC-Based Electroactive Polymers
    Olsen, Zakai J.
    Kim, Kwang J.
    FRONTIERS IN ROBOTICS AND AI, 2019, 6
  • [47] MODELING EVOLUTION OF MICROSTRUCTURES BENEATH TOPOGRAPHICALLY TEXTURED SURFACES PRODUCED USING SHEAR BASED MATERIAL REMOVAL
    Basu, Saurabh
    Wang, Zhiyu
    Saldana, Christopher
    PROCEEDINGS OF THE ASME 11TH INTERNATIONAL MANUFACTURING SCIENCE AND ENGINEERING CONFERENCE, 2016, VOL 2, 2016,
  • [48] Modeling and Simulation of Flow and Uranium Isotopes Separation in Gas Centrifuges Using Implicit Coupled Density-Based Solver in OpenFOAM
    Ghazanfari, Valiyollah
    Salehi, Ali Akbar
    Keshtkar, Ali Reza
    Shadman, Mohammad Mahdi
    Askari, Mohammad Hossein
    EUROPEAN JOURNAL OF COMPUTATIONAL MECHANICS, 2020, 29 (01): : 1 - 26
  • [49] Combining artificial intelligence and physics-based modeling to directly assess atomic site stabilities: from sub-nanometer clusters to extended surfaces
    Lamoureux, Philomena Schlexer
    Choksi, Tej S.
    Streibel, Verena
    Abild-Pedersen, Frank
    PHYSICAL CHEMISTRY CHEMICAL PHYSICS, 2021, 23 (38) : 22022 - 22034
  • [50] 6D Pose Estimation for Flexible Production with Small Lot Sizes based on CAD Models using Gaussian Process Implicit Surfaces
    Lin, Jianjie
    Rickert, Markus
    Knoll, Alois
    2020 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), 2020, : 10572 - 10579