Title :
An Light-weight Algorithm for Unorganized Point Cloud
Author :
Jing, Zhang ; Qiwei, He ; Shaowei, Feng
Author_Institution :
Office of R&D, Naval Univ. of Eng., Wuhan, China
Abstract :
In order to improve entity reverse building, a light weight algorithm is proposed to reduce the mass of cloud data. Firstly a model of unorganized point cloud are improved to compact with an octree and principle component analysis. A PCA (principle component analysis) is carried out to prove that features of the local surface defined by points in a leaf node can be detected. For a specific feature in a leaf node of the octree, a simplification algorithm is propose to sample points form the unorganized points cloud. The results of the new algorithm show that the new algorithm is very effiecient.
Keywords :
Internet; feature extraction; octrees; principal component analysis; reverse engineering; cloud data mass; entity reverse building; leaf node; light weight algorithm; octree; principle component analysis; unorganized point cloud; Algorithm design and analysis; Clouds; Eigenvalues and eigenfunctions; Feature extraction; Octrees; Pediatrics; Principal component analysis; octree; reverse engineering; simplification; unorganized point cloud;
Conference_Titel :
Electronic Commerce and Security (ISECS), 2010 Third International Symposium on
Conference_Location :
Guangzhou
Print_ISBN :
978-1-4244-8231-3
Electronic_ISBN :
978-1-4244-8231-3
DOI :
10.1109/ISECS.2010.51
