Due to the shortages of current methods for the recovery of sharp features of mesh models with holes,this paper presents two novel algorithms for the recovery of features(especially sharp features)in mesh models.One a...Due to the shortages of current methods for the recovery of sharp features of mesh models with holes,this paper presents two novel algorithms for the recovery of features(especially sharp features)in mesh models.One algorithm defines an energy that is regarded as the difference between the initial features and the ideal features.The optimal solution of the energy optimization problem modifies the initial features.The algorithm has good performance on sharp features.The other method establishes a plane cluster for each initial feature point to obtain a corresponding modified feature point.If necessary,we can obtain the modified feature line by fitting these modified points.Both methods depend little on the result of fillingmodel holes and result in better features,which maintain the sharp geometric characteristic and the smoothness of the model.The experimental results of the two algorithms demonstrate their superiority and rationality compared with the existing methods.展开更多
This paper presents a reconstruction algorithm to build a surface mesh approximating an object from an unorganized point sampling of the boundary object. It combines 3D Delaunay tetrahedralization and mesh-growing met...This paper presents a reconstruction algorithm to build a surface mesh approximating an object from an unorganized point sampling of the boundary object. It combines 3D Delaunay tetrahedralization and mesh-growing method and uses only once Delau- nay triangulation. It begins with 3D Delaunay triangulation of the sampling. Then initialize the surface mesh with seed facets se- lected from Delaunay triangulation. Selection is based on the angle formed by the circumscribing ball of incident tetrahedral. Finally, grow until complete the surface mesh based on some heuristic rules. This paper shows several experimental results that demonstrate this method can handle open and close surfaces and work efficiently on various object topologies except non-manifold surface with self-intersections. It can reproduce even the smallest details of well-sampled surfaces but not work properly in every under-sampled situation that point density is too low.展开更多
基金The authors are supported by a NKBRPC(2011CB302400)the National Natural Science Foundation of China(11171322 and 11371341)the 111 Project(No.b07033).
文摘Due to the shortages of current methods for the recovery of sharp features of mesh models with holes,this paper presents two novel algorithms for the recovery of features(especially sharp features)in mesh models.One algorithm defines an energy that is regarded as the difference between the initial features and the ideal features.The optimal solution of the energy optimization problem modifies the initial features.The algorithm has good performance on sharp features.The other method establishes a plane cluster for each initial feature point to obtain a corresponding modified feature point.If necessary,we can obtain the modified feature line by fitting these modified points.Both methods depend little on the result of fillingmodel holes and result in better features,which maintain the sharp geometric characteristic and the smoothness of the model.The experimental results of the two algorithms demonstrate their superiority and rationality compared with the existing methods.
基金Supported by National Natural Science Foundation of China(No.60875046)Program for Changjiang Scholars and Innovative Research Team in University(No.IRT1109)+5 种基金the Key Project of Chinese Ministry of Education(No.209029)the Program for Liaoning Excellent Talents in University(No.LR201003)the Program for Liaoning Science and Technology Research in University(No.LS2010008,2009S008,2009S009, LS2010179)the Program for Liaoning Innovative Research Team in University(Nos.2009T005, LT2010005, LT2011018)Natural Science Foundation of Liaoning Province(201102008)"Liaoning Bai Qian Wan Talents Program(2010921010, 2011921009)"
文摘This paper presents a reconstruction algorithm to build a surface mesh approximating an object from an unorganized point sampling of the boundary object. It combines 3D Delaunay tetrahedralization and mesh-growing method and uses only once Delau- nay triangulation. It begins with 3D Delaunay triangulation of the sampling. Then initialize the surface mesh with seed facets se- lected from Delaunay triangulation. Selection is based on the angle formed by the circumscribing ball of incident tetrahedral. Finally, grow until complete the surface mesh based on some heuristic rules. This paper shows several experimental results that demonstrate this method can handle open and close surfaces and work efficiently on various object topologies except non-manifold surface with self-intersections. It can reproduce even the smallest details of well-sampled surfaces but not work properly in every under-sampled situation that point density is too low.
基金Supported in part by the National Basic Research Program of China (Grant No. 2004CB318000)the National High-Tech Research & Development Program of China (Grant Nos. 2006AA01Z301, 2006AA01Z302, 2007AA01Z336)Key Grant Project of Chinese Ministry of Education (Grant No. 103001)