Fast implicit surface reconstruction method based on normal constraints

Abstract

In this paper, a new procedure for implicit surface reconstruction from oriented points is presented. A normal constraints based implicit polynomials fitting method and the partition of unity approach are fused into our framework. Firstly, a large scale input data is subdivided into some overlapping patches by octree. Then the global implicit surface is transferred into local implicit patch fitting and blending of them. To fit the local implicit polynomials, we build an energy by three steps corresponding to enforcement of the interpolatory constraints, satisfying of normal constraints and enhancement of fitting stability. The unkowns in an implicit polynomial are determined by minimizing this quadratic energy function. It is demonstrated in some experiments with several real data sets that this combination provides an intuitive and effective means to approximate the scattered point data associated normals.

Calibration Method of Orthogonally Splitting Imaging Pose Sensor Based on KDFcmPUM

“…RBF interpolation is used to display local features in the sub-domains, then local features are restored globally by a weight function. This method is widely used in image segmentation [16,17,18] and three-dimensional surface reconstruction [19,20,21]. Different methods have been proposed to partition the domain and construct the weight function to improve the PUM’s management of large scattered data.…”

Untitled

“…The complexity of many geometric operations greatly depends on the method of representation. Some information related to most commonly method of representing surfaces such as implicit (Guo et al, 2010;De Araújo et al, 2015;Akenine et al, 2018), parameterized B-spline and NURBS (Lim & Haron, 2014;Zhang 2016;Bhattarai et al, 2017) are also taken into account. The parameterized form is more natural for designing and representing shape in the computer as compared to implicit (Brigger et al, 2000).…”