Automated Detection of 3D Roof Planes from Lidar Data

DEMİR N.

JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING, cilt.46, sa.8, ss.1265-1272, 2018 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 46 Sayı: 8
  • Basım Tarihi: 2018
  • Doi Numarası: 10.1007/s12524-018-0802-2
  • Dergi Adı: JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.1265-1272
  • Anahtar Kelimeler: LIDAR, 3D modeling, Point cloud, Computational geometry, BUILDING MODELS, RECONSTRUCTION, EXTRACTION, IMAGES
  • Akdeniz Üniversitesi Adresli: Evet

Özet

The purpose of this study is to derive vectoral 3D roof planes from the LIDAR point cloud of the detected buildings. For segmentation of the LIDAR point cloud, the RANSAC algorithm has been used. Because the RANSAC algorithm is sensitive to the used parameters, and results in over- or under-segmentation of the clusters, a refinement method has been proposed. The detection of roof planes has been improved with use of the refinement method. Therefore, similar plane surfaces have been combined, followed by the region-growing algorithm, to split the under-segmented plane surfaces. The digitization of the roof boundaries is performed using the alpha-shapes algorithm, followed by line fitting to generalize the roof edges. The quality assessment has been done using the reference vector dataset with comparison using four different criteria.