Reconstruction of 3D laser scanned point clouds may generate a mesh characterized by a high number of triangles. Unfortunately, in Computer Aided Design environments neither a simple triangle reduction, nor decimation filters are feasible for mesh optimization, because of their intrinsic errors. In this paper we show how Genocop III can be effectively used to reconstruct a point cloud bounding the error under a certain threshold. Moreover, we define an optimized algorithm for evaluating the reconstruction error, that exploits AABB-trees and pre-computation and provides a useful metric to the genetic algorithm.
An Evolutionary Optimization Method for Parameter Search in 3D Points Cloud Reconstruction / Bevilacqua, V; Ivona, F; Cafarchia, D; Marino, F. - STAMPA. - 7995:(2013), pp. 601-611. [10.1007/978-3-642-39479-9_70]
An Evolutionary Optimization Method for Parameter Search in 3D Points Cloud Reconstruction
Bevilacqua V;Marino F
2013-01-01
Abstract
Reconstruction of 3D laser scanned point clouds may generate a mesh characterized by a high number of triangles. Unfortunately, in Computer Aided Design environments neither a simple triangle reduction, nor decimation filters are feasible for mesh optimization, because of their intrinsic errors. In this paper we show how Genocop III can be effectively used to reconstruct a point cloud bounding the error under a certain threshold. Moreover, we define an optimized algorithm for evaluating the reconstruction error, that exploits AABB-trees and pre-computation and provides a useful metric to the genetic algorithm.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.