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| Format: | Artículo científico |
| Language: | en |
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Universidade Federal do Paraná
2020
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| Online Access: | https://www.redalyc.org/articulo.oa?id=393962953004 |
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Table of Contents:
- MODELING OF ROOFS FROM POINT CLOUDS USING GENETIC ALGORITHMS Natália Sabariego Jorge Antonio Silva Centeno Ciencias de la Tierra LIDAR Point clouds Roof modeling Genetic algorithms Light Detection And Ranging Building roof extraction has been studied for more than thirty years and it generates models that provide important information for many applications, especially urban planning. The present work aimed to model roofs only from point clouds using genetic algorithms (GAs) to develop a more automatized and efficient method. For this, firstly, an algorithm for edge detection was developed. Experiments were performed with simulated and real point clouds, obtained by LIDAR. In the experiments with simulated point clouds, three types of point clouds with different complexities were created, and the effects of noise and scan line spacing on the results were evaluated. For the experiments with real point clouds, five roofs were chosen as examples, each with a different characteristic. GAs were used to select, among the points identified during edge detection, the so-called ‘significant points’, those which are essential to the accurate reconstruction of the roof model. These points were then used to generate the models, which were assessed qualitatively and quantitatively. Such evaluations showed that the use of GAs proved to be efficient for the modeling of roofs, as the model geometry was satisfactory, the error was within an acceptable range, and the computational effort was clearly reduced. 2020 artículo científico 1413-4853 https://www.redalyc.org/articulo.oa?id=393962953004 10.1590/s1982-21702020000100004 en http://www.redalyc.org/revista.oa?id=3939 Boletim de Ciências Geodésicas application/pdf Universidade Federal do Paraná Boletim de Ciências Geodésicas (Brasil) Num.1 Vol.26