Fractional- order T- S fuzzy predictive control based free- form Surface reconstruction

2019 ◽  
Vol 79 (23-24) ◽  
pp. 16955-16966
Author(s):  
Guo Yan-chun
Keyword(s):  
Surface Reconstruction ◽  
Fractional Order ◽  
Predictive Control ◽  
Free Form ◽  
Free Form Surface ◽  
Fuzzy Predictive Control

A clustering approach to free form surface reconstruction from multi-view range images

2009 ◽  
Vol 27 (6) ◽  
pp. 725-747 ◽  
Author(s):  
Hong Zhou ◽  
Yonghuai Liu ◽  
Longzhuang Li ◽  
Baogang Wei
Keyword(s):  
Surface Reconstruction ◽  
Free Form ◽  
Range Images ◽  
Clustering Approach ◽  
Free Form Surface

Free-form surface reconstruction

2020 ◽  
pp. 93-127
Author(s):  
X. Jane Jiang ◽  
Paul J. Scott
Keyword(s):  
Surface Reconstruction ◽  
Free Form ◽  
Free Form Surface

Free Form Surface Reconstruction Method Based on LS-SVM

2011 ◽  
Vol 308-310 ◽  
pp. 280-283
Author(s):  
Fu Zhong Wu
Keyword(s):  
Surface Reconstruction ◽  
Approximation Error ◽  
Engineering Application ◽  
Least Square ◽  
Free Form ◽  
Support Vector ◽  
Surface Model ◽  
Reconstruction Method ◽  
Svm Model ◽  
Free Form Surface

A free form surface reconstruction method based on least square support vector regression is presented. Firstly in order to eliminate noise points, some sample points are chosen from the measured data to construct LS-SVM model. Thus a LS-SVM model to approximate the measured points is obtained. And the distribution probability of the approximation error is figured out. In result, the noise points are eliminated when their error probability is less than the specified threshold value. Then the boundary points are extracted. Lastly the surface model is reconstructed by use of the measured points from which noise points have been eliminated. The results indicate that the reconstruction precision can satisfy the demands of engineering application.

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