633 
APPLICATION OF ROBUST REGRESSION 
FOR EXTERIOR ORIENTATION OF VIDEO IMAGES 
N. Fukaya a *, T. Anai a , H. Sato a , N. Kochi a , M. Yamada a , H. Otani b 
a Imaging Laboratory, R&D Center, Topcon Corporation, 75-1 Hasunuma Itabasi Tokyo, Japan 
-n fukaya@topcon .co.jp 
b Surveying Instruments Div, Topcon Corporation, 75-1 Hasunuma Itabasi Tokyo, Japan 
ICWG III/V 
KEYWORDS: Orientation, Video, Adjustment, Tracking, Bundle, Exterior, Algorithms 
ABSTRACT: 
Nowadays, the 3-D measurement system using the video image sequences has been used in many fields, for example the vision 
sensor for machine control or the measurement technique of city area for GIS or landscape simulation. However, the robust 
estimation of the exterior orientation parameters for each video frames is still important issues. In recent years, the authors have been 
concentrating for development of 3D measurement system using video image sequences with robust tracking and robust exterior 
orientation. However, some problems should be resolved for this systems goal, such as limitation for camera movement, robustness 
of bundle adjustment. Therefore, the authors are developing the new algorithm of robust exterior orientation for video image 
sequences using robust regression procedure. In this paper, authors describe the effectiveness of robust exterior orientation method 
for video image sequences which developed by authors. Moreover, application for 3D measurement of this algorithm is also 
described. 
1. INTORDUCTION 
In order to perform the 3D measurement using video image 
sequences from the platform moving freely, the technique of 
exterior orientation for each video frame is still important issue. 
In the field of general photogrammetry, the exterior orientation 
is performed using many control points that have accurate 3D 
coordinate. In addition, the position and rotation sensor such as 
GPS or gyro sensors are used in the real-time application field 
of 3D measurement from video image sequences recently. 
However, the construction of accurate control point generally 
needs a lot of time and labor. In the case of GPS, the accuracy 
of positioning is depending on GPS satellite position and 
condition of the environment, and the positioning at inside of 
structure is particularly impossible. Similarly, the high accurate 
gyro sensor’s cost is still expensive. In addition, high accurate 
synchronization in time axis between these sensors and video 
camera is necessary, and it becomes the rise in size or cost of 
system. 
From these backgrounds, automatic estimation technique of the 
exterior orientation parameters from video image sequences 
without using the above-mentioned equipments has become 
important issue in late years, and many research groups had 
shown the studies and applications [l,2,3 7 
On the other hand, the authors have developed PC-based 3D 
Image Measuring Station called PI-3000, and many applications 
of 3D measurement using consumer digital still cameras have 
been achieved previously. This system can estimate the interior 
orientation parameters of consumer digital still camera 
accurately. Furthermore, this system can perform bundle 
adjustment with many images simultaneously. Therefore, 
exterior orientation parameter of camera and 3D coordinate of 
object can be obtained in high accuracy [4,5 \ 
From circumstances mentioned above, the authors have been 
concentrating for development of the 3D measurement system 
using consumer video camera with robust tracking and robust 
exterior orientation method. In this method, in order to perform 
the automatic rejection for error correspondences of natural 
feature points in each video frames, tracking process and 
relative orientation process in exterior orientation procedure 
performed robust regression based on the LMedS (Least 
Median of Square) method. However, in this exterior orientation 
procedure, there is a limitation for movement of a camera 
because of the limit of relative orientation procedure. In 
addition, the robustness of relative orientation is insufficient 
when there is the big change of the scene such as the structure 
comer [6] . 
Therefore, in order to resolve these problems, the authors are 
developing the new algorithm of robust exterior orientation for 
video image sequences. 
In this paper, authors describe the effectiveness of algorithms of 
robust exterior orientation for video image sequences, and 
application for volume measurement from video image 
sequences is also described. 
2. EXTERIOR ORIENTATION PROCEDURE FROM 
VIDEO IMGAE SEAQUENCES 
2.1 Main Flow of Exterior Orientation Procedure 
The exterior orientation procedure in this system consists of the 
tracking process and bundle adjustment process. The tracking 
process performs the extraction of natural feature points from 
video image sequences and tracking the natural feature points. 
As the result of tracking process, corresponding points in each 
video frames are obtained. Finally, bundle adjustment for all