Fast Reconstruction Algorithm of Point Cloud Implicit Surface

2021 ◽  
Vol 58 (4) ◽  
pp. 0415003
Author(s):  
王连哲 Wang Lianzhe ◽  
韩俊刚 Han Jungang ◽  
卢升 Lu Sheng ◽  
唐海鹏 Tang Haipeng ◽  
齐全 Qi Quan ◽  
...  
Keyword(s):  
Point Cloud ◽  
Reconstruction Algorithm ◽  
Implicit Surface ◽  
Fast Reconstruction

A Fast Reconstruction of Dense Unorganized Point Cloud Based on 3-Color Octree

2009 ◽  
Vol 628-629 ◽  
pp. 293-298 ◽  
Author(s):  
H.M. Zhou ◽  
Z.G. Liu ◽  
M.X. Li ◽  
B.H. Lu
Keyword(s):  
Point Cloud ◽  
Reconstruction Algorithm ◽  
Point Clouds ◽  
Watershed Algorithm ◽  
Triangular Meshes ◽  
Boundary Node ◽  
Model Based ◽  
Implicit Model ◽  
Interior Boundary ◽  
Fast Reconstruction

This paper describes a fast reconstruction algorithm of implicit model based on 3-color octree structure for dense unorganized point cloud. At first, the point cloud is stored with an extended octree, 3-color octree. Aiming at this 3-color octree structure a new node watershed algorithm is presented with a higher efficiency to estimate the signs of subdivided leaf nodes. So the leaf nodes are divided into three types: interior, boundary and exterior nodes. To quickly reconstruct the model we sample the 3-color octree structure only at boundary nodes, which greatly reduces the number of sampled points. Then, the triangular meshes are extracted according to the relationships of boundary node. Finally the applications are illustrated in several point clouds, which shows the efficiency and precision of this reconstruction algorithm.

Research on Digital Modeling about Free-Form Surface with Holes Based on Coordinate Measuring Machine

2011 ◽  
Vol 287-290 ◽  
pp. 2805-2809
Author(s):  
Ming Yu Huang ◽  
Xiu Juan Wu ◽  
Zhong Shi Jia ◽  
Hong Jun Ni ◽  
Jing Jing Lv ◽  
...  
Keyword(s):  
Point Cloud ◽  
Coordinate Measuring Machine ◽  
Free Form ◽  
Model Reconstruction ◽  
Contact Measurement ◽  
Digital Modeling ◽  
Measuring Machine ◽  
Fast Reconstruction ◽  
Free Form Surface ◽  
Free Form Surfaces

Data acquisition and model reconstruction of free-form surfaces with holes were been studied, based on coordinate measuring machines. First, the structural process of the parts was analyzed, the method of combinate contact measurement with non-contact measurement were used to get point cloud; Then the point cloud were been preprocessed, feature curve extracted and solid modeled; Finally, the restructure model was been quality assessed and accuracy assessed. Using the measurement of combinated contact and non-contact can also meet both the precision requirement of key part and the fast reconstruction requirement of non-critical part, which has great significance on that part to fast and accurate reconstruction.

scholarly journals Scattered Point Cloud Data Reconstruction Algorithm Based on Local Convexity

2020 ◽  
Author(s):  
Sorush Niknamian
Keyword(s):  
Point Cloud ◽  
Reconstruction Algorithm ◽  
Large Error ◽  
Small Error ◽  
Data Reconstruction ◽  
Point Cloud Data ◽  
Local Convexity ◽  
Cloud Data ◽  
Time Consumption ◽  
Local Connection

Point cloud data reconstruction is the basis of point cloud data processing. The reconstruction effect has a great impact on application. For the problems of low precision, large error, and high time consumption of the current scattered point cloud data reconstruction algorithm, a new algorithm of scattered point cloud data reconstruction based on local convexity is proposed in this paper. Firstly, according to surface variation based on local outlier factor (SVLOF), the noise points of point cloud data are divided into near outlier and far outlier, and filtered for point cloud data preprocessing. Based on this, the algorithm based on local convexity is improved. The method of constructing local connection point set is used to replace triangulation to analyze the relationship of neighbor points. The connection part identification method is used for data reconstruction. Experimental results show that, the proposed method can reconstruct the scattered point cloud data accurately, with high precision, small error and low time consumption.

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