Normal estimation algorithm fuzzily to classify three-dimensional point clouds
A normal estimation algorithm could be used to any shape model,because existing normal estimation algorithms were only suitable to some shape models.The point clouds of the model were classified by fuzzy inference systems.The fuzzy rulers were given according to the distribute characters and curvature change of point clouds.Three-dimensional point clouds were divided three categories,including smooth,thin and sharp shapes.The normal estimation algorithm of every kind of point was given.Because the shape distribution of the model was different,the called numbers of corresponding normal estimation algorithm were different after classifying too.The denture model was used to evident the algorithm.Compared with three typical algorithms,the algorithm can estimate the normal and construct the denture more accurate,efficient and simple.
three-dimensional point cloudsfuzzy inferencenormal estimationsmooth shapesharp shapethin shape
国家科技期刊平台
NSTL
万方数据
维普
