AN INTERACTIVE SCHEME FOR BUILDING MODELING USING THE 
SPLIT-MERGE-SHAPE ALGORITHM 
: ar rs o + : 
Jiann-Yeou Rau” , Liang-Chien Chen’, Guam-Hua Wang“ 
* Associate Research Engineer, " Professor, © Student 
CSRSR, National Central University, 300 Jung-Da Rd. JhongLi City, Taoyuan, TAIWAN 320, 
(jyrau, lechen, victor)@esrsr.neu.edu.tw 
Commission PS WG III/7 
KEYWORDS: Three-dimensional, GIS, Urban, City, Building, Algorithms, Semi-automation, Feature. 
ABSTRACT: 
The most important feature in urban modeling is the 3D building model. It is essential in many applications, such as 3D GIS, cyber city, 
true-orthophoto generation, etc. Due to the huge demand of 3D building model, an effective solution for geometrical building 
modeling is required. In this paper, a 3D building modeling based on the Split-Merge-Shape (SMS) algorithm is presented. Since the 
SMS algorithm adapts 3D visible roof-edges for building modeling, a semi-automatic scheme for measuring 3D visible roof-edges 
from multi-view aerial images is proposed. In the SMS algorithm, the SPLIT and MERGE steps are the procedures for topology 
reconstruction from isolated roof-edges. The SHAPE step uses the available roof-edge height information to define an appropriate 
rooftop. With the SMS method, the topographic mapping of buildings, and geometric building modeling, can be seamlessly integrated 
into a unified procedure. In the paper, we will start with an overview of state-of-the-art technologies on the subject of building 
modeling. The SMS algorithm is then presented and integrated with the proposed semi-automatic scheme for 3D roof-edges 
measurement. A preliminary test utilizing a set of four 1:5,000 aerial images is demonstrated. Experimental results indicate that high 
reliability and accuracy may be reached with limited manual efforts. 
1. INTRODUCTION 
Since the 3D building model is the most important feature in 
urban area, the creation of 3D virtual world from remote sensed 
data is getting more attention during the last decade. Many 
kinds of remote sensing data, such as 2D stereo images and 
LIDAR, were adapted as data source by most of the researchers. 
The generated 3D building model is essential in many 
applications, such as true-orthophoto generation (Rau & Chen, 
2002), map revision, cartographic database compilation, change 
detection, transportation, urban planning, environmental 
planning (Lange, 1999), geo-visualization (Keim ef al., 2004), 
flight simulations, noise and air pollution simulations, 
microclimate studies, wireless networks telecommunication 
planning (Siebe & Buning, 1997; Leberl, ef al., 1999), virtual 
tourism information querying (Volz & Klinec, 1999), etc. An 
effective solution for the generation of reliable and accurate 
building models is thus more urgent than ever. The related 
techniques can be generalized as 3-D mapping. 
Since 3-D mapping technology is getting important, some 
Digital Photogrammetric Workstations (DPWs) have developed 
new functions that will create DBMs directly, and integrate 
them into topographic mapping. However, image occlusion is 
still the biggest problem in the manual delineation process. The 
operator is responsible for the measurement of roof corners and 
the structuring of building models. Whenever image occlusions 
occur, the operator has to estimate the hidden corners from 
conjugate images. The whole process is time-consuming and 
labor intensive, as well as tedious, inefficient and produces with 
a limited accuracy, especially for connected buildings in densely 
built-up areas. Additionally, the designed DPWs need special 
hardware and software for stereo viewing and measurement. For 
example, they need a stereo-monitor, a high-end stereographic 
display card, a set of hand wheel and foot plate for measurement, 
etc. The cost will increase the budget of a company and 
withdraw their competition advantageous. 
R Corresponding author. 
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Except for the above manual operations necessary for building 
modelling in some DPWs, most of the related work can be 
categorized into two approaches, according to the degree of 
human intervention required for topological reconstruction. The 
two approaches are the automatic approach (Baillard. and 
Zisserman, 2000; Fischer, et al, 1998; Henricsson, 1998) and 
the semi-automatic approach (Gülch, et al, 1999; Grün & 
Wang, 1998). 
Gülch, es al. (1999) proposed the use of monocular images and 
building-based measurements for 3-D city model creation. Their 
approach is based on a semi-automatic scheme. In manual 
modelling, the operator’s task is to fit a wire-frame building 
model, which is selected from a predefined model database, to 
the images, via monoscopic viewing. The operator has to adjust 
the wire-frame model to fit the corresponding image features. A 
complex building is decomposed into some basic building types 
and constructed using a Constructive Solid Geometry (CSG) 
tree. The operator is also responsible for handling the CSG tree 
structures. Although the approach is innovative, the operator 
takes too heavy a responsibility, necessitating a qualified 
operator. The approach may be efficient for simple structure and 
specific type of building, but not for groups of connected 
buildings in densely built-up areas where occlusions and 
shadows frequently occur. 
Grün & Wang (1998) proposed a topology builder, i.e. the 
CC-Modeler system, for the generation of building models. The 
system is based on a semi-automatic approach, utilizing 
manually measured 3-D point clouds. The measurement of 3-D 
point clouds, denoting all roof corners must be complete, 
including any hidden ones. The system is a model-based 
approach, but it can be applied to general objects, such as roads, 
rivers, parking lots, ships, etc. During data acquisition, 3-D 
point clouds are manually coded as boundary points and interior 
points, according to their functionality and structure. Although 
the system is operational, some of their limitations cannot be 
ignored. Those limitations are stated as follows. (1) The 
measurement of hidden corners caused by building occlusions is 
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