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Research On Decomposition And Extraction Of Object Based On Skeleton

Posted on:2018-12-20Degree:MasterType:Thesis
Country:ChinaCandidate:C FuFull Text:PDF
GTID:2518306248982909Subject:Software engineering
Abstract/Summary:PDF Full Text Request
The decomposition and extraction of model components are of great significance for model interaction editing,model matching and retrieval,parametric texture mapping,geometric deformation,animation and point cloud reconstruction.The current three-dimensional model decomposition methods are mostly carried out for the grid model with topological relations.In this paper,the component decomposition and extraction of point cloud model are studied.The main work is summarized as follows.(1)The normalization and normalization of discrete point sets are realized.The Kd-Tree is established for each point on the original point cloud model,and the nearest neighbor is used to find the normal vector of the point by using the least squares fitting plane.Then,by determining the direction of the coordinate The normal vector of the maximum point is used as the benchmark,and the normal direction of the point cloud model is normalized.(2)A method of extracting coarse skeleton of object based on shrinkage strategy is given.Based on the iterative contraction of the normal vector in the opposite direction,the contraction model of the approximate skeleton is obtained,which lays the foundation for the solution of the latter step skeleton topology.(3)A method of building a coarse skeleton topology based on clustering is implemented.The clustering center is used to solve the clustering center point by using K-means clustering model,and the central point of the secondary connection is to form a topological map based on Euclidean distance and the topology is optimized.(4)This paper presents a method of decomposing object components with key points and skeleton points.The partition point and the surface of the model surface are calculated.The optimal partition plane is constructed by dividing the point and its adjacent ridge points.The original model is decomposed by dividing the plane and the skeleton.The results of this paper enriched the method of space cognition of the machine,and played a good supporting role in the application of animation animation,computer vision and other fields.
Keywords/Search Tags:Normal vector, shrink, K-means clustering, Ridge valley point, Decomposition
PDF Full Text Request
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