ISPRS Commission III, Vol.34, Part 3A „Photogrammetric Computer Vision“, Graz, 2002 
  
SURFACE MODELLING OF URBAN 3D OBJECTS FROM 
VEHICLE-BORNE LASER RANGE DATA 
Huijing Zhao, Ryosuke Shibasaki 
University of Tokyo 
Commission III, WG III/7 
KEY WORDS: Laser Range Scanner, Vehicle-borne, Marching Cube, Urban 3D Model, Reconstruction 
ABSTRACT: 
In this paper, a method is presented to generate surface model of urban out-door environment using vehicle-borne laser range 
scanners, which have been developed in Konno ef al.[11]. A classification is conducted first, where range points are divided into the 
groups of vertical building surface, road surface, other surface, window, tree and others, unknown objects. Erroneous measurement 
are corrected, e.g. window data or discarded, e.g. irregular data. Volumetric modelling and marching cube method are exploited in 
this research to model both surface-structured objects, e.g. building and road surface, and volume-structured objects, e.g. tree. 
Estimates for signed distance are proposed. Through an experiment, it is demonstrated that urban out-door environment can be 
reconstructed with high automation and efficiency using our method. 
1. INTRODUCTION 
Up to now, many research groups in photogrammetry 
community have been devoted to the analysis of aerial based 
imageries for the reconstruction of 3D urban object (e.g. [5,10]). 
Normally, aerial survey can cover relatively wide area, but fail 
in capturing details of urban objects such as sidewall (facade) of 
buildings. On the other hand, most of the existing systems in 
computer vision field have been demonstrated at small scales, 
using simple objects, under controlled light condition. (e.g. 
[1,6,15]). With the development of automobile navigation 
system, 3D GIS (Geographic Information System), and 
applications using virtual and augmented reality, details of 
urban out-door objects are found to be of importance, as user 
viewpoints are involved on the ground, not in the air. An 
efficient reconstruction method exploiting ground-based survey 
technique at large scale, for complicated and unexpected object 
geometries, under uncontrolled light condition is required. 
Several systems aiming at generating 3D model of real world 
have been developed during the last few years. According to the 
major data source being used for reconstructing object geometry, 
the systems can be broadly divided into two groups. One is 
called image-based approach. Another is called range-based 
approach. 
In the first group, 3D model of urban scene is reconstructed 
using still or moving images. Image-based approach is also 
called in-direct approach since object geometry has to be 
automatically or human-assistedly extracted using stereo or 
motion techniques. Debevec, et al. [3] presented an interactive 
method of modelling and rendering architectural scenes from 
sparse sets of still photographs, where large architectural 
environment can be modelled with far fewer photographs than 
using other full-automated image-based approaches. MIT City 
Scanning Project [9] developed a prototype system of 
automatically reconstructing textured geometric CAD model of 
urban environment using spherical mosaic images, where 
camera's position and orientation of each spherical image is 
first initialised using positioning sensors, then refined through 
image matching. Geometric representation is extracted either 
using feature correspondence or by identifying vertical facades. 
Uehara and Zen [12] proposed a method of creating textured 3D 
map from existing 2D map using motion technique, where a 
video camera is mounted on a calibrated vehicle and the image 
streams that captured are geo-referenced to the existing 2D map 
using GPS data. Through the above research efforts, it is 
demonstrated that image-based approach can be used in 
reconstructing 3D model of urban out-door environment. 
Whereas, the difficulties in reliable stereo matching, distortion 
from limited resolution and unstable geometry of CCD cameras 
are the major obstacles to reconstruct a 3D model of 
complicated environment with necessary accuracy and 
robustness. 
In the second group, 3D model of urban scene is reconstructed 
using range image. Range-based approach is also called direct 
approach since object geometry can be directed measured using 
range scanner. In recent years, as the development of laser 
technique, range scanners using eye-safe laser with high 
accuracy, large range distance and high measurement frequency 
are being used for the modelling of urban environment. 
Sequeira et al.[14] and El-Hakim et al.[4] developed systems 
on reconstructing indoor environment of rather large scale. 
Stamos and Allen [17], Zhao and Shibasaki [20] aimed at 
generating 3D model of urban out-door objects. In these 
systems, range scanners are mounted on stationary platforms 
(called stationary system). Range images produced by the 
systems are typically rectangular grids of range distances (or 3D 
coordinates after conversion) from the sensor to the objects 
being scanned. Objects are measured from a number of 
viewpoints to reduce occlusions, where location and direction 
of viewpoints are unknown or roughly obtained using GPS, 
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