Back to Search Start Over

Automatic Extraction Method of 3D Feature Guidelines for Complex Cultural Relic Surfaces Based on Point Cloud.

Authors :
GENG, Yuxin
ZHONG, Ruofei
HUANG, Yuqin
SUN, Haili
Source :
Journal of Geodesy & Geoinformation Science; Mar2024, Vol. 7 Issue 1, p16-41, 26p
Publication Year :
2024

Abstract

Cultural relics line graphic serves as a crucial form of traditional artifact information documentation, which is a simple and intuitive product with low cost of displaying compared with 3D models. Dimensionality reduction is undoubtedly necessary for line drawings. However, most existing methods for artifact drawing rely on the principles of orthographic projection that always cannot avoid angle occlusion and data overlapping while the surface of cultural relics is complex. Therefore, conformal mapping was introduced as a dimensionality reduction way to compensate for the limitation of orthographic projection. Based on the given criteria for assessing surface complexity, this paper proposed a three-dimensional feature guideline extraction method for complex cultural relic surfaces. A 2D and 3D combined factor that measured the importance of points on describing surface features, vertex weight, was designed. Then the selection threshold for feature guideline extraction was determined based on the differences between vertex weight and shape index distributions. The feasibility and stability were verified through experiments conducted on real cultural relic surface data. Results demonstrated the ability of the method to address the challenges associated with the automatic generation of line drawings for complex surfaces. The extraction method and the obtained results will be useful for line graphic drawing, displaying and propaganda of cultural relics. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20965990
Volume :
7
Issue :
1
Database :
Complementary Index
Journal :
Journal of Geodesy & Geoinformation Science
Publication Type :
Academic Journal
Accession number :
178409792
Full Text :
https://doi.org/10.11947/j.JGGS.2024.0103