RANSAC-BASED SEGMENTATION FOR BUILDING ROOF FACE DETECTION IN LiDAR POINT CLOUD

Autor(es)

Dal Poz, Aluir Porfirio ; Yano, Michelle Sayuri ; IEEE

• Tipo de documento: Artigo Científico
• Fonte: IGARSS 2018 - 2018 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM; v. N/A, p. 4-pg., 2018-01-01.

Resumo

This work proposes a method for segmenting the roof planes of buildings in Light Detection and Ranging (LiDAR) data. First, a preprocessing of the point cloud is performed to separate the points belonging to each building. The RANdom SAmple Consensus (RANSAC) method is then used in each building region to identify sets of coplanar points belonging to the roof faces. Finally, planar segments representing the same roof face are connected to minimize the fragmentation that may occur in the previous step. This requires the use of techniques for analyzing the continuity of adjacent planar segments. Although several thresholds are required, they can be predetermined or adapted, thus avoiding their modification by an operator in each application of the method. The results show that the proposed method functions appropriately, rarely failing in regions affected by local structures such as trees and antennas. Consequently, average rates higher than 90% were obtained for completeness and correction. (AU)

• Processo FAPESP: 13/16452-8 - Segmentação de telhados de edifícios em dados de varredura a LASER usando técnicas de processamento de imagem e o método RANSAC
• Beneficiário: Michelle Sayuri Yano
• Modalidade de apoio: Bolsas no Brasil - Mestrado