FEATURE BASED IMAGE ORIENTATION AND OBJECT RECONSTRUCTION 
Günter Strunz 
Chair for Photogrammetry and Remote Sensing 
Technical University Munich 
Arcisstraße 21, D-8000 Munich 2 
Germany 
Commission III 
ABSTRACT: 
Image orientation and object reconstruction tasks in photogrammetry are generally based on distinct points. 
However, in 3D object space besides points there are also lines (straight or curved) and surfaces (planar or curved), 
which are increasingly being available in digital data bases, and in 2D image space lines can be extracted, especially 
when automatic procedures of image analysis are used. These geometric features in object space and their 
projections into image space can be used for image orientation and object reconstruction. 
In this paper a systematic overview concerning the use of points, lines and surfaces for photogrammetric orientation 
and object reconstruction tasks is given. It is shown, which tasks can be performed, and the respective minimum 
number of features needed for a solution is derived. Some remarks on degenerate configurations are given and the 
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evaluation of precision using general geometric features is shown by means of simulated examples. 
KEY WORDS: Image orientation, general geometric features, feature based photogrammetry. 
1. INTRODUCTION 
The transition from analytical to digital photo- 
grammetry, which is one of the major topics in 
photogrammetric research, requires the modification 
and extension of the existing models and the develop- 
ment of completely new concepts. For the geometric 
tasks of photogrammetry this basically means that the 
photogrammetric observations in image space do not 
result from human measurements, but from automatic 
techniques of image analysis. In the traditional 
approach image orientation and object reconstruction 
tasks are more or less completely based on distinct 
points. However, geometric features in object space 
can also be straight or curved lines and planar or 
curved surfaces. (Note: the term lines refers to one- 
dimensional curves including both straight and curved 
continuous features, i.e. it is not restricted to straight 
lines). These features and their projection into image 
space can be used for image orientation and object 
reconstruction. Especially for digital techniques of 
image analysis this aspect is essential, because lines 
are easier to extract than point features by automatic 
procedures. Therefore a sound theory is necessary for 
dealing with general geometric features. 
Research and practical work based on the correspon- 
dence of general geometric features, besides points, is 
being performed in computer vision and photo- 
grammetry. Some references are given in the follow- 
ing, which represent important work done in this field. 
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Horizontal and vertical lines were used as control 
features for close range applications in Dóhler (1975). 
Kager, Kraus (1976) described the mathematical 
model for plumb lines, straight lines, parallel and 
orthogonal lines and planes in a simultaneous 
adjustment of photogrammetric, geodetic and so- 
called fictitious observations. The concept of line to 
line correspondence in aerial photogrammetry was 
shown by Masry (1981) and Lugnani (1982). The 
rectification of SPOT imagery using points and edges 
as control was presented by Paderes et al. (1984). 
Space resection based on straight line correspon- 
dences was shown in Dhome et al. (1989), Liu et al. 
(1990) and Chen (1991). The formulation of the 
mathematical model for the solution of space resec- 
tion and intersection using line features was given in 
Mulawa, Mikhail (1988); further work was published 
in Sayed, Mikhail (1990). Relative orientation of a 
sequence of images using correspondences of straight 
line features was treated e.g. in Yen, Huang (1983), 
Liu, Huang (1988a, 1988b), Spetsakis, Aloimonos 
(1990) and Weng et al. (1992). In these approaches 
the computation of the rotation and position para- 
meters is separated and non-linear as well as linear 
algorithms are derived. In Kubik (1991) relative and 
absolute orientation using linear features was dis- 
cussed. Finsterwalder (1991) presented algorithms and 
geometric explanations for the use of lines in space 
resection, rectification and absolute orientation. 3D to 
3D matching of corresponding lines and surfaces was 
published by Faugeras, Hebert (1986), Kim, Aggarwal