International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B5. Istanbul 2004
Feature Extraction And Modeling Of Urban Building From Vehicle-Borne Laser Scanning Data
B.L Lit Q0. Li. 7. Shi, F.F.Wu
(1. Center of Spatial Information and Network Communication, Wuhan University, 430079, Wuhan, PR China,
lee(@)wtusm.edu.cn 2.Advanced Research Center for Spatial Information Technology, Department of Land surveying
and Geo-Informatics, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China;)
KEY WORDS: Laser Scanning; Algorithms; Feature; Modeling; Extraction; Urban
ABSTRACT:
Laser scanning is playing an important role in an acquisition of the 3D spatial objects in urban because of real-time and high
efficiency than traditional methods. The research presented in this paper is focused on segmentation of range image, especially
captured by vehicle-borne laser scanning systems, which is the crucial technology for extracting objects from laser scanned data.
Here, a method, named as Density of Projected Points (DoPP) is proposed for the range image segmentation. With such a process,
it is possible for feature extraction, object classification and modeling without other auxiliary data. An experimental study is
conducted to demonstrated the feasibility of the proposed solution on urban building object extraction.
1. INTRODUCTION
Geo-spatial information technology is one of the focuses of
research of worldwide countries nowadays, and the acquisition,
processing and application of information are the three themes.
The technology of high speed acquisition and automatic
processing of spatial data is a crux need to be solved urgently in
the field of Digital Earth. In the late 1980s, laser-scanning
technology gained important improvement in the real-time
capture of 3D spatial information, which provided an option for
the acquisition of high resolution spatial information, and
enabled people to capture data moving from point by point
traditionally to continuous automatically. Laser-scanning
survey technology is not restricted by weather, and it directly
captures high precision 3D data in uncontacted active survey
way. It has superiority which tranditional survey technology
cannot substitute,and it has been developed as an important
supplement of photogrammetry and remote sensing.
Based on the difference of mounting platforms, laser-scanning
systems were classified into Airborne Laser Scanning System
(ALSS; also called Laser Range Finder, LRF; or Airborne
Laser Terrain Mapper, ALTM) [Flood 1997, Killian 1996] and
Ground-based Laser Scanning System (GLSS; or Vehicle-borne
Laser Mapping System, VLMS) [Li 2000,Li 2003].
ALSS is a multi-sensor integrated complex system, and it has
been gradually matured [Ackermann 1999]. Currently in the
world there are some systems as follows: the TopEye system
from the Saab Survey in Sweden, ALTMS from Optech in
Canada, the Fli-Map developed in the U.S. by John E. Chance,
and TopSys and TopScan from Germany. Airborne
laser-scanning technology has extensive application in surveys
of sagging power lines [Wehr 1999], and surveys of coastlines
and forests [Kraus 1998], mine fields, and urban areas [Kraus
1998, Erik 1997, Haala 1997, Murakami 1998].
The products and application of the GLSS for data capture are
still at developing stage. Based on the style of data capture, it
can be divided into both static-scanning and mobile-scanning.
The typical product of static-scanning is the Cyrax serials from
Leica. Mobile scanning system such as the sample vehicle
developed by Tokyo University [Manandhar 2001], which
consists of three laser scanners and six line cameras, is mainly
applied in the data capture and modeling of city buildings and
roads. Hi-Tech Research and Development Program of China
(Project 863) has successively funded — vehicle-borne
laser-scanning survey technology [Lu 2003].
Data captured by laser scanning are called "Range Image" or
"Points cloud" which consists of discrete vector points. The
range image captured by close-range and high-resolution
consists of abundant features: both topographic and ground
objects information. So it is possible for us to extract feature
according to height information besides constructing
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