Full text: CMRT09

In: Stilla U, Rottensteiner F, Paparoditis N (Eds) CMRT09. IAPRS, Vol. XXXVIII, Part 3/W4 — Paris, France, 3-4 September, 2009 
Karim Hammoudi, Fadi Dornaika and Nicolas Paparoditis 
Université Paris-Est, Institut Géographique National, Laboratoire MATIS 
73 Avenue de Paris, 94160 Saint-Mandé Cedex, France 
{firstname.lastname} @ign.fr 
KEY WORDS: 3D Point Cloud, Hough Transform, RANSAC Method, I\-means Clustering, Laser Scanner, Building Footprint, 
Building Reconstruction, City Modeling. 
In this paper, we address the problem of generating building footprints using terrestrial laser scanning from a Mobile Mapping System 
(MMS). The MMS constitutes a fast and adapted tool to extract precise data for 3D city modeling. Urban environments evolve over 
time due to human activities and other factors. Buildings are constructed or destroyed and the urban areas are extended. Therefore, the 
structures of the cities are constantly modified. Currently, building footprints can be generated using aerial data. However, aerial based 
footprints lack precision due to the nature of the data and to the associated extraction methods. The use of MMS is proposed as an 
alternative to perform this complex task. In this work, we propose an operational approach for automatic extraction of accurate building 
footprints. We describe the challenges associated with the terrestrial laser raw data acquired in realistic and dense urban environments. 
After a filtering stage on the 3D laser cloud point, we extract and reconstruct the dominant facade planes by combining the Hough 
transform, the fc-means clustering algorithm and the RANSAC method. The building footprint is then estimated from these dominant 
planes. Preliminary experimental results are presented and discussed. The assessments show that this approach is very promising for 
the automation of building footprints extraction. 
Nowadays, city modeling has become an important subject of 
research for architectural lasergrammetry, photogrammetry and 
computer vision communities. There is an increasing need for 
3D building descriptions in urban areas in several fields of ap 
plication like city planning and virtual tourism. Therefore many 
research activities on city modeling have focused on the auto 
matic generation of 3D building models from aerial images. Most 
pipelines which have been developed recover the 3D shape of 
roof surfaces, but building ground footprints come from existing 
databases acquired by the digitization and vectorization of cadas 
tral maps or from surveying measurements. 
Initially, the building footprints are extracted either in an auto 
matic way using the aerial data (Cheng et al., 2008), (Tarsha Kurdi 
et al., 2006) or in a manual way requiring many surveyors to make 
measurements in the terrain. However, these footprint databases 
sometimes do not exist (e.g., in less developed countries, etc.), 
can be very difficult to obtain (e.g., in areas with difficult access 
or prohibited overflights), or can even be of insufficient geomet 
rical quality with respect to some applications. Moreover, the 
automatic building footprints extraction using aerial images is a 
hard task. Imprecise and/or incomplete focusing will affect the 
modeling process in the sense that the final 3D building model 
will lack accuracy and details. 
Recent progress in technologies have allowed the development 
and the construction of devices for rapid acquisition of 3D car 
tographic terrestrial data with very high precision in urban envi 
ronments. The Mobile Mapping System allows an easy coverage 
of large scale areas such as districts and cities. The feasibility of 
this kind of system has been demonstrated (Haala et al., 2008), 
and the usage of this device is increasingly widespread for ap 
plications like the conservation of patrimony (Baz et al., 2008) 
or visualization. Many works using terrestrial laser scanning are 
particularly focused on segmenting and texturing the building fa 
cades (Boulaassal et al., 2007), (Pu, 2008). 
This ground-based modeling is thus unavoidable for some ap 
plications such as facade texturing where images acquired by a 
ground based system need to be registered relatively to the aerial 
3D model to ensure a satisfactory mapping. Matching the street 
level images with the 3D aerial model is an extremely complex 
due to the generalization problems. The data acquired by ground- 
based 3D data collection systems, can be used to extract and 
model facades that can advantageously replace the ground foot 
prints in the aerial reconstruction process, thus leading to a co 
herent use of both aerial and terrestrial data. 
This paper focuses on the first step of a global 3D facade recon 
struction framework, i.e. the extraction of the facade footprints 
and planes. The MMS constitutes an alternative and reliable tool 
which can be useful to obtain building footprints with very high 
accuracy and details. The aim of this study is to propose an oper 
ational approach for automated building footprints extraction in 
urban environments. The remainder of the paper is organized as 
follows: Section 2 states the problems related to the raw laser data 
and their processing. Section 3 presents the proposed approach 
for extracting the building’s footprints and facade planes. Section 
4 gives some promising experimental results. 
In this study, we use a mobile mapping system for acquiring geo- 
referenced 3D laser point clouds. The Terrestrial Laser Scanning 
system (TLS system) is a 2D profile scanner. The third dimension 
is induced by the vehicle displacement. In addition to this, the 
Mobile Mapping System is equipped with a Global Positioning 
System (GPS), an Inertial Measurement Unit (IMU) and a Dis 
tance Measuring Instrument (DMI), namely an odometer. This

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