Robust recovery of 3d geometric primitives from point cloud

Xiang Yang, Hae Gea

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A robust method for surface fitting in 3D point cloud is presented as an application of the robust estimation of multiple inlier structures algorithm [1]. The geometric primitives such as planes, spheres and cylinders are detected from the point samples in the noisy dataset, without regenerating surface normals or mesh. The inlier points of different surfaces are classified and segmented, with the tolerance of error for each surface estimated adaptively from the input data. From the segmented points, designers can interact with the geometric primitives conveniently. Direct modification of 3D point cloud and inverse design of solid model can be applied. Both synthetic and real point cloud datasets are tested for the use of the robust algorithm.

Original languageEnglish (US)
Title of host publication37th Computers and Information in Engineering Conference
PublisherAmerican Society of Mechanical Engineers (ASME)
ISBN (Electronic)9780791858110
DOIs
StatePublished - Jan 1 2017
EventASME 2017 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2017 - Cleveland, United States
Duration: Aug 6 2017Aug 9 2017

Publication series

NameProceedings of the ASME Design Engineering Technical Conference
Volume1

Other

OtherASME 2017 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2017
CountryUnited States
CityCleveland
Period8/6/178/9/17

Fingerprint

Point Cloud
Recovery
Surface Fitting
Normal Surface
Sample point
Solid Model
Robust Algorithm
Robust Estimation
Robust Methods
Tolerance
Mesh

All Science Journal Classification (ASJC) codes

  • Mechanical Engineering
  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design
  • Modeling and Simulation

Cite this

Yang, X., & Gea, H. (2017). Robust recovery of 3d geometric primitives from point cloud. In 37th Computers and Information in Engineering Conference [67564] (Proceedings of the ASME Design Engineering Technical Conference; Vol. 1). American Society of Mechanical Engineers (ASME). https://doi.org/10.1115/DETC2017-67564
Yang, Xiang ; Gea, Hae. / Robust recovery of 3d geometric primitives from point cloud. 37th Computers and Information in Engineering Conference. American Society of Mechanical Engineers (ASME), 2017. (Proceedings of the ASME Design Engineering Technical Conference).
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Yang, X & Gea, H 2017, Robust recovery of 3d geometric primitives from point cloud. in 37th Computers and Information in Engineering Conference., 67564, Proceedings of the ASME Design Engineering Technical Conference, vol. 1, American Society of Mechanical Engineers (ASME), ASME 2017 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2017, Cleveland, United States, 8/6/17. https://doi.org/10.1115/DETC2017-67564

Robust recovery of 3d geometric primitives from point cloud. / Yang, Xiang; Gea, Hae.

37th Computers and Information in Engineering Conference. American Society of Mechanical Engineers (ASME), 2017. 67564 (Proceedings of the ASME Design Engineering Technical Conference; Vol. 1).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Yang X, Gea H. Robust recovery of 3d geometric primitives from point cloud. In 37th Computers and Information in Engineering Conference. American Society of Mechanical Engineers (ASME). 2017. 67564. (Proceedings of the ASME Design Engineering Technical Conference). https://doi.org/10.1115/DETC2017-67564