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Vision based 3D city modelling by using airborne laser scanner data for urban GIS

Segmentation
Imprecisely, segmenting a range/laser radar image is the process of labelling the pixels so that pixels whose measurements are of the same surface are given the same label. The segmentation algorithm adopted here can be characterised as an example of the common approach to region segmentation by iteratively growing from seed regions suggested by Hoover et al [12]. The segmenter works by computing a planar fit for each pixel and then growing regions whose pixels have similar plane equations. A two-stage process is used to compute a pixel’s normal. First, a growing operation is performed from the pixel, bounded by an N ´ N window. To join a bordering four-connected pixel must be within Tperp range units. This has the effect of separating “outliers” from “inliers” (with respect to the central pixel), where the outliers could be across a jump edge, or simple noise.

If less than 50% of the pixels within the window are inliers, then a single plane equation is fit to the pixels. If 50% or more of the pixels within the window are inliers, then a set of nine plane equations are computed using edge preserving sub-masks of the inliers in the N ´ N window. Improvement of this procedure is underway. Roof polygons obtained are shown in figure 8 (b).

ALS image DSM products and Applications
Some of the results of generated DSM of urban areas are shown in figure 9 (a-f). 3D Urban model form ideal completion of a GIS database. They are the appropriate data source for: - 1. primary acquisition of the building structure; 2. town planning applications including 3-D-visualisation of new buildings in the existing environment; 3.simulation: of transmitter placement for telecommunication, line of sight analyses; of air flow, pollution and noise distribution; of surface water flows to improve air quality by avoiding and eliminating “hot”-spots, areas of high concentrations of exhaust gases and reduced fresh-air supply (microclimate modelling).

Other applications include Emergency and Defence (Counter terrorism operations, Surveillance, Road traffic accident mapping, Crime scene forensic imaging, Disaster planning and scene pickup, Nuclear accident assessment), Engineering & Architecture (City council fixed asset management, Road surveys, Rail surveys, Water course analysis, Infrastructure survey - bridges, buildings, Urban environment impact studies, As-built compared with design survey, Site mapping) and Entertainment (Virtual set design for movie, Actor, equipment planning for movie production 3D gaming development, Virtual museum, Virtual tour guide Production).

Summary
This research explicated the automatic construction of building surface models of 3D-scene from laser scanner data. ALS data smoothening has been performed by noise removal filter called median_SUSAN. The detection, thinning and vectorization of Building boundary edges followed this. Segmentation of ALS data was performed to extract roof regions. Both the boundary and roof edges were vectorised and polygons representing buildings have been obtained.

Acknowledgements
The authors appreciate the research and funding facilities provided by the Japan Science and Technology (JST) and Softopia Japan, Japan. Mr. Kawano, Gifu University was very helpful in the computational part of this research.

References

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