Entropic Method for 3D Point Cloud Simplification

  • Abdelaaziz Mahdaoui
  • A. Bouazi
  • A. Marhraoui Hsaini
  • E. H. Sbai
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 37)


To represent the surface of complex objects, the samples resulting from their digitization can contain a very large number of points. Simplification techniques analyse the relevance of the data. These simplification techniques provide models with fewer points than the original ones. Whereas reconstruction of a surface, with simplified point cloud, must be close to the original. In this article, we develop a method of simplification based on the concept of entropy, which is a mathematical function that intuitively corresponds to the amount of information this allows considering only relevant points.


Simplification Entropy 3D point cloud Density estimator Mesh quality Compactness 



The Max Planck, Atene and Tennis shoe models used in this paper are the courtesy of AIM@SHAPE shape repository.


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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Department of Physics, Faculty of ScienceMoulay Ismail UniversityMeknesMorocco
  2. 2.Ecole Supérieure de TechnologieMoulay Ismail UniversityMeknesMorocco

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