| Revue: | Boletim de ciencias geodesicas |
| Base de datos: | PERIÓDICA |
| Número de sistema: | 000458672 |
| ISSN: | 1413-4853 |
| Autores: | Sabariego, Natalia1 Centeno, Jorge Antonio Silva2 |
| Instituciones: | 1Universidade Federal do Parana, Programa de Pos-graduacao em Ciencias Geodesicas, Curitiba, Parana. Brasil 2Universidade Federal do Paraná, Departamento de Geomática, Curitiba, Paraná. Brasil |
| Año: | 2020 |
| Volumen: | 26 |
| Número: | 1 |
| País: | Brasil |
| Idioma: | Inglés |
| Tipo de documento: | Artículo |
| Enfoque: | Analítico, descriptivo |
| Resumen en inglés | 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 |
| Disciplinas: | Geociencias, Ingeniería |
| Palabras clave: | Geodesia, Urbanismo, Modelación de techos, Algoritmos genéticos, Nubes de puntos, LIDAR |
| Keyword: | Geodesy, Urbanism, Roof modeling, Genetic algorithms, Point clouds, LIDAR |
| Texte intégral: | Texto completo (Ver HTML) Texto completo (Ver PDF) |
