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Feature Extraction from 3D Point Cloud Data Based on Discrete Curves
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-19, 19 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-04-03
Country of Publication
Egypt
No. of Pages
19
Main Subjects
Abstract EN
Reliable feature extraction from 3D point cloud data is an important problem in many application domains, such as reverse engineering, object recognition, industrial inspection, and autonomous navigation.
In this paper, a novel method is proposed for extracting the geometric features from 3D point cloud data based on discrete curves.
We extract the discrete curves from 3D point cloud data and research the behaviors of chord lengths, angle variations, and principal curvatures at the geometric features in the discrete curves.
Then, the corresponding similarity indicators are defined.
Based on the similarity indicators, the geometric features can be extracted from the discrete curves, which are also the geometric features of 3D point cloud data.
The threshold values of the similarity indicators are taken from [0,1], which characterize the relative relationship and make the threshold setting easier and more reasonable.
The experimental results demonstrate that the proposed method is efficient and reliable.
American Psychological Association (APA)
An, Yi& Li, Zhuohan& Shao, Cheng. 2013. Feature Extraction from 3D Point Cloud Data Based on Discrete Curves. Mathematical Problems in Engineering،Vol. 2013, no. 2013, pp.1-19.
https://search.emarefa.net/detail/BIM-1008949
Modern Language Association (MLA)
An, Yi…[et al.]. Feature Extraction from 3D Point Cloud Data Based on Discrete Curves. Mathematical Problems in Engineering No. 2013 (2013), pp.1-19.
https://search.emarefa.net/detail/BIM-1008949
American Medical Association (AMA)
An, Yi& Li, Zhuohan& Shao, Cheng. Feature Extraction from 3D Point Cloud Data Based on Discrete Curves. Mathematical Problems in Engineering. 2013. Vol. 2013, no. 2013, pp.1-19.
https://search.emarefa.net/detail/BIM-1008949
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1008949