Non Local Point Set Surfaces

Author(s):  
Thierry Guillemot ◽  
Andres Almansa ◽  
Tamy Boubekeur

Author(s):  
M. Alexa ◽  
J. Behr ◽  
D. Cohen-Or ◽  
S. Fleishman ◽  
D. Levin ◽  
...  
Keyword(s):  


2012 ◽  
Vol 55 (9) ◽  
pp. 2075-2089 ◽  
Author(s):  
YongWei Miao ◽  
Jonas Bösch ◽  
Renato Pajarola ◽  
M. Gopi ◽  
JieQing Feng
Keyword(s):  


2008 ◽  
Vol 32 (2) ◽  
pp. 221-234 ◽  
Author(s):  
Erik Hubo ◽  
Tom Mertens ◽  
Tom Haber ◽  
Philippe Bekaert


2007 ◽  
Vol 26 (3) ◽  
pp. 23 ◽  
Author(s):  
Gaël Guennebaud ◽  
Markus Gross


Author(s):  
Lanfang Miao ◽  
Jin Huang ◽  
X. Liu ◽  
Hujun Bao ◽  
Qunsheng Peng ◽  
...  
Keyword(s):  


2011 ◽  
Vol 43 (8) ◽  
pp. 957-970 ◽  
Author(s):  
Yu Liu ◽  
Xiaoping Qian


2014 ◽  
Vol 565 ◽  
pp. 253-259
Author(s):  
Yu Liu

This paper constructs PSSs (Point Set Surfaces) by combining locally fitted quadric polynomials. First, an energy function is defined as the weighted sum of distances from a point to these quadric polynomials. Then, a vector field is constructed by the weighted sum of normal vectors at input points. Finally, points on a PSS are obtained by finding local minima of the energy function along the vector field. Experiments demonstrate that high quality PSSs can be obtained from the method presented for input point clouds sampled from various shapes.



2017 ◽  
Vol 37 (1) ◽  
pp. 60-70 ◽  
Author(s):  
Azzouz Hamdi-Cherif ◽  
Julie Digne ◽  
Raphaëlle Chaine


Author(s):  
Pinghai Yang ◽  
Xiaoping Qian

Rapid advancement of 3D sensing techniques has lead to dense and accurate point cloud of an object to be readily available. The growing use of such scanned point sets in product design, analysis and manufacturing necessitates research on direct processing of point set surfaces. In this paper, we present an approach that enables the direct layered manufacturing of point set surfaces. This new approach is based on adaptive slicing of moving least squares (MLS) surfaces. Salient features of this new approach include: 1) it bypasses the laborious surface reconstruction and avoids model conversion induced accuracy loss; 2) the resulting layer thickness and layer contours are adaptive to local curvature and thus it leads to better surface quality and more efficient fabrication; 3) the MLS surface naturally smoothes the point cloud and allows up-sampling and down-sampling, and thus it is robust even for noisy or sparse point sets. Experimental results of the slicing algorithm on both synthetic and scanned point sets are presented.



2007 ◽  
Vol 23 (6) ◽  
pp. 433-443 ◽  
Author(s):  
Chunxia Xiao ◽  
Wenting Zheng ◽  
Yongwei Miao ◽  
Yong Zhao ◽  
Qunsheng Peng


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