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A flexible framework for surface reconstruction from large point sets Remi All`egre
 

Summary: A flexible framework for surface reconstruction from large point sets
R´emi All`egre
, Rapha¨elle Chaine, Samir Akkouche
LIRIS UMR 5205 CNRS / Universit´e Lyon 1, Villeurbanne, F-69622, France
Abstract
This paper presents a flexible method to reconstruct
simplified mesh surfaces from large unstructured point
sets, extending recent work on dynamic surface recon-
struction. The method consists of two core components:
an efficient selective reconstruction algorithm, based on
geometric convection, that simplifies the input point set
while reconstructing a surface, and a local update al-
gorithm that dynamically refines or coarsens the recon-
structed surface according to specific local sampling
constraints.
A new data structure is introduced that significantly
accelerates the original selective reconstruction algo-
rithm and makes it possible to handle point set models
with millions of sample points. This data structure
mixes a kd-tree with the Delaunay triangulation of

  

Source: Allègre, Rémi - Département Informatique, Université de Strasbourg
Chaine, Raphaëlle - Laboratoire d'InfoRmatique en Image et Systèmes d'information, Université Claude Bernard (Lyon I)

 

Collections: Computer Technologies and Information Sciences