Delaunay growth algorithm based on point cloud curvature smoothing improvement

Ruiqi Huang; Hanyu Hong

doi:10.1117/12.2538134

14 February 2020 Delaunay growth algorithm based on point cloud curvature smoothing improvement

Ruiqi Huang, Hanyu Hong

Proceedings Volume 11430, MIPPR 2019: Pattern Recognition and Computer Vision; 114300L (2020) https://doi.org/10.1117/12.2538134
Event: Eleventh International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2019), 2019, Wuhan, China

Abstract

In order to meet the requirements of 3D reconstruction in accuracy, reconstruction speed and algorithm applicability, this paper proposes a Delaunay growth algorithm based on point cloud curvature smoothing, which firstly projects a 3D discrete point cloud into a 2D plane and passes a 2D Delaunay triangulation. The two-dimensional Delaunay triangulation is performed by the empty circle criterion and the maximum and minimum angle criterion in the score. The PCA principal component analysis is used to estimate the normal of the three-dimensional point cloud and locate the normal on the same side to avoid the disordered points. The cloud normal, combined with the curvature of the corresponding 3D point cloud, removes the invalid normal in the point cloud due to invalid points and preserves the larger part of the point cloud as much as possible, and finally passes the Delaunay constraint criterion and the evaluation function. Filter the set of alternate points to ensure that the reconstructed triangle approximates the Delaunay triangle. The experimental results show that the reconstruction algorithm proposed in this paper is much better than the traditional greedy triangle projection algorithm and Poisson algorithm and the reconstruction speed is increased by 20%.

Citation Download Citation

Ruiqi Huang and Hanyu Hong "Delaunay growth algorithm based on point cloud curvature smoothing improvement", Proc. SPIE 11430, MIPPR 2019: Pattern Recognition and Computer Vision, 114300L (14 February 2020); https://doi.org/10.1117/12.2538134

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
8 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Clouds

Reconstruction algorithms

Principal component analysis

3D modeling

3D image reconstruction

3D image processing

Detection and tracking algorithms

Show All Keywords

Keywords/Phrases

Search In:

Publication Years