International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B3, 2012 
XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia 
IMAGE TO POINT CLOUD METHOD OF 3D-MODELING 
A.G. Chibunichev, V.P. Galakhov. 
Moscow State University of Geodesy and Cartography, #4, Gorokhovsky pereulok, 105064, 
Moscow, Russia. agchib@mail.ru, vpgal@mail.ru 
KEY WORDS: Photogrammetry, Laser scanning, Photography, Three-dimensional, Fusion, Modeling. 
ABSTRACT: 
This article describes the method of constructing 3D models of objects (buildings, monuments) based on digital images and a point 
cloud obtained by terrestrial laser scanner. The first step is the automated determination of exterior orientation parameters of digital 
image. We have to find the corresponding points of the image and point cloud to provide this operation. Before the corresponding 
points searching quasi image of point cloud is generated. After that SIFT algorithm is applied to quasi image and real image. SIFT 
algorithm allows to find corresponding points. Exterior orientation parameters of image are calculated from corresponding points. 
The second step is construction of the vector object model. Vectorization is performed by operator of PC in an interactive mode using 
single image. Spatial coordinates of the model are calculated automatically by cloud points. In addition, there is automatic edge 
detection with interactive editing available. Edge detection is performed on point cloud and on image with subsequent identification 
of correct edges. Experimental studies of the method have demonstrated its efficiency in case of building facade modeling. 
1. INTRODUCTION 
One of the most frequent tasks for land survey is high detailed 
survey of building facades, monuments and objects of cultural 
heritage. The purpose of this survey is to obtain detailed model 
of object’s interior and exterior. Several different kinds of 
survey can be used to obtain model satisfying these demands. In 
this paper we’ll discuss two methods: photogrammetric 
processing of digital images and terrestrial laser scanning with 
further modeling. These methods could be compared in 
application to facade modeling. 
The process of image capturing is simple and fast, though needs 
planning of total image captures and their relative positions. 
Absolute and relative tie points are needed to create 
photogrammetric model, therefore additional method of survey 
is used to achieve coordinates of absolute tie points. Quality and 
precision of modeling based on photogrammetric processing of 
photographic images in high degree depends on experience and 
qualification of PC operator and furthermore on his 
physiological abilities. 
Terrestrial laser scanning needs much more time for capturing 
spatial data, because a laser scanner needs to be placed on a 
tripod, prepared for scanning and only after that scanning could 
be started, which is not as fast as simple image capturing. 
Absolute tie points are needed for increasing of total model 
precision or for referencing to external coordinate system, but 
total quantity of tie points is less then for photogrammetric 
model. Precision and quality of modeling by the point cloud 
much less depends on qualification and experience of PC 
operator. But operator should perform several different kinds of 
manipulations with parameters of point cloud projection onto 
2D surface of screen (rotation, translation, scaling) before 
operator get concept of object in his imagination. 
Practical experience shows advantages and disadvantages of 
these methods (Fabris, Achilli, Artese 2009). 
Cost of good enough digital camera is low comparing to 
terrestrial laser scanning system and obviously camera can be 
added into kit. Using combination of these two methods 
complementing each other allows resulting model quality 
increasing and reducing time efforts (Jansa J., Studnicka N., 
Forkert G., Haring A., Kager H., 2004). 
These two methods could be combined on several different 
levels. 
The first, easiest, level of combination is coloring of cloud 
points according to digital image colors. Naturally laser scanner 
is capturing point coordinates and intensity of returned laser 
beam (Chunmei Hu, Yanmin Wang, Wentao Yu, 2008). 
Coloring of cloud points makes easier process of data 
perception by PC operator. 
The next level is creation of the digital surface model from 
cloud points, orthophototransformation of digital images and 
surface texturing. Efficiency of this level is higher. 
Furthermore, operator can vectorize orthophoto in 2D and then 
project vectors onto 3D, because the surface model can be used 
as DTM for orthophoto (Ayman Zureiki, Michel Roux, 2009). 
Lines, extracted automatically from orthophoto, could also be 
projected onto DTM surface. But the quality of projecting 
depends on quality of created surface model. In case of 
terrestrial laser scanning captured point clouds contain many 
“noise” points due to great number of obstructions in natural 
environments. Point clouds needed to be filtered and cleaned 
from “noise” points before surface modeling. Every “noise” 
point leads to incorrect surface modeling and thus to incorrect 
orthophototransformation of digital images. But filtering is not 
enough. Breaklines should be created for accurate surface 
modeling. All these operations need labor input from operator. 
New methods of modeling developed to solve these problems. 
Nex and Rinaudo (2009) proposed new approach of automatic 
modeling using digital images and point cloud processing. On 
the first step bundle block adjustment and edge extraction 
performed for digital images. After that edge extraction 
performed for point cloud using extracted image edges. 
New method of vectorization proposed in this article. The 
method is based on vectorization by single untransformed 
images. Automatic image and point cloud segmentation is 
performed. Segments are used for edge extraction. Extracted 
edges are transposed onto images and onto quasi images 
generated from point cloud. SIFT operator used for tie point 
extraction. Tie points are used for calculation of exterior 
orientation parameters of images. After image referencing edges 
could be projected onto image plane. Matching edges are left as 
vectors. Operator of PC manually creates new vectors by single