Modeling urban LIDAR point clouds with combined 2D TIN and 3D tetrahedron structure

Jun Wu; Honggang Liao; Menmen Chen; Zhiyong Peng

doi:10.1117/12.2031094

27 October 2013 Modeling urban LIDAR point clouds with combined 2D TIN and 3D tetrahedron structure

Jun Wu, Honggang Liao, Menmen Chen, Zhiyong Peng

Proceedings Volume 8919, MIPPR 2013: Pattern Recognition and Computer Vision; 891912 (2013) https://doi.org/10.1117/12.2031094
Event: Eighth International Symposium on Multispectral Image Processing and Pattern Recognition, 2013, Wuhan, China

Abstract

This paper presents our research on exploring the combined 2D TIN and 3D Tetrahedra structure to quickly model large-range Urban LIDAR point clouds for 3D visualization purpose. To this end, Morphological grayscale reconstruction is first implemented to segment LIDAR point clouds into terrain and non-terrain regions. After that, segmented Lidar terrain points are modeled with Constrained Delaunay Triangulation under constrain of building boundary as well as non-terrain points are modeled with Power Crust algorithm to obtain reconstructed building surface. Next, two kinds of model are combined based on shared building boundary. Finally, 3D visualization of selected urban area with presented technique clearly demonstrates higherefficiency. Valuable conclusions are given as well.

Citation Download Citation

Jun Wu, Honggang Liao, Menmen Chen, and Zhiyong Peng "Modeling urban LIDAR point clouds with combined 2D TIN and 3D tetrahedron structure", Proc. SPIE 8919, MIPPR 2013: Pattern Recognition and Computer Vision, 891912 (27 October 2013); https://doi.org/10.1117/12.2031094

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KEYWORDS

3D modeling

LIDAR

Clouds

Image segmentation

Tin

Visual process modeling

3D visualizations

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