Mixed simplification algorithm of point clouds
Dehui Kong · Computer Engineering and Applications Journal · 2007
Point-cloud simplifications often adopt single clustering or iterative schemes.In this paper,combines the advantages of both.First,a processing of uniform clustering is performed for the point-cloud model,and then iterative simplification is used to further simplify the initially simplified model.In order to effectively combine the two schemes,uses quadric error matrix to transform related information between the two steps in the whole process.For the model with boundary,this paper presents a simple and effective method for detecting the boundary.Experimental results show that the quality of the simplified models using our method is superior to the uniform clustering method,and close to the iterative method.But the memory footprint and simplifying time are far below than the iterative method.