Dynamic 3D Models with Local and Global Deformations: Deformable Superquadrics
IEEE Transactions on Pattern Analysis and Machine Intelligence
Cluster Analysis and Priority Sorting in Huge Point Clouds for Building Reconstruction
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 01
Watertight scenes from urban LiDar and planar surfaces
SGP '13 Proceedings of the Eleventh Eurographics/ACMSIGGRAPH Symposium on Geometry Processing
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Surface reconstruction from implicit data of sub-randomly distributed 3D points is the key work of extracting explicit information from LiDAR data. This paper proposes an approach of extended snake theory to surface reconstruction from LiDAR data. The proposed algorithm approximates a surface with connected planar patches. Growing from an initial seed point, a surface is reconstructed by attaching new adjacent planar patches based on the concept of minimizing the deformable energy. A least-squares solution is sought to keep a local balance of the internal and external forces, which are inertial forces maintaining the flatness of a surface and pulls of observed LiDAR points bending the growing surface toward observations. Experiments with some test data acquired with a ground-based LiDAR demonstrate the feasibility of the proposed algorithm. The effects of parameter settings on the delivered results are also investigated.