Normal Estimation for Mass Point Clouds of Irregular Model in the 3D Reconstruction based on Fuzzy Inference

다국어 초록 (Multilingual Abstract)

This paper presents a fuzzy normal estimate for mass point clouds of irregular models in reconstruction. The irregular model is complex object that some part is smooth and some parts are irregular including sharp features. Therefore, we put kNN and curvature of mass point clouds to fuzzy inference system to divide the kind of point clouds and the output of FIS can determine which part of tooth point clouds belong to. For different kinds point clouds, corresponding algorithm is given. Point clouds in the smooth area are estimated normal by PCA directly and ones in other regions of thin or sharp area are estimated by checker and attach points. This method is simpler than those complex methods used on the whole point clouds directly. The experiment results show that much time is saved and surface reconstruction is very fine than PCA and WLOP.

목차 (Table of Contents)

• Abstract
• 1. Introduction
• 2. FIS Applied in Normal Estimation of Mass Point Clouds
• 3. Fuzzy Normal Estimate Method for Point Clouds of Irregular Model
• 3.1. The Character of Irregular Model
• 3.2. Description of Fuzzy Rules
• 3.3. Normal Estimation Framework
• 4. Experimental Results
• 5. Conclusions
• Acknowledgment
• References