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Technical Commission VII

International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B7, 2012
XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia

T. Anai ^ *, T. Sasaki *, K. Osaragi *, M. Yamada *. F. Otomo *, H. Otani ^
* R&D Center, TOPCON CORPORATION, 75-1, Hasunuma, Itabashi, Tokyo —t.anai@topcon.co.jp
Positioning Business Unit, TOPCON CORPORATION, 75-1, Hasunuma, Itabashi, Tokyo
Commission V, ICWG V/I
KEY WORDS: Automation, Exterior Orientation, Matching, Video, Tracking, GPS, Robust
In this paper, we propose the automatic exterior orientation procedure for the Low-cost Unmanned Aerial Vehicle (UAV)
photogrammetry. The Low-cost UAV has become useful tool for low altitude photogrammetry from the rapidly increasing of
automatic control technique in past several years. However, automatic exterior orientation is still important issue. The most
important point of automatic exterior orientation is the automatic detection of corresponding points in each still image. For this goal,
the authors have developed the automatic corresponding point detection technique using both video Image and still images. The
video image of this investigation is obtained with still images simultaneously. Therefore, the tracking result of video image gives
robust correspondence information between each still image. Moreover, the exterior orientation procedure using GPS information
from UAV and minimum ground control points have been investigated. This paper is structured as follows. At the first we describe
the over view of automatic exterior orientation procedure in this investigation. As the next, the details of tracking of common feature
points and robust bundle adjustment are described. Also, accuracy assessment of this automatic exterior orientation procedure is
described. Finally some conclusion is given.
The aerial triangulation in photogrammetry using mass images
taken by the Low-cost UAV has become possible easily by
rapidly increasing of automatic flight control technique of Low-
cost UAV in These past several years. The Low-cost UAV
which integrated GPS and IMU usually has ability to perform
autonomous flight and automatic navigation along planned
waypoints. These waypoints are usually planned beforehand
easily by dedicated software as considering the camera
parameter, area of interest, overlap of image, altitude and so on.
Moreover, still images at planned waypoints are acquired
automatically by digital still camera mounted on UAV.
Therefore, Low-cost UAV system is widely used as the useful
platform in the low altitude application field of photogrammetry
such as agriculture, archaeology, traffic monitoring, and disaster
area surveying (Remondino, 2011). However, in order to
perform the fully automatic aerial triangulation using mass still
image in low altitude application field, some problems have to
be resolved. The automatic detection of corresponding point
from common features visible in each still image is the most
important problem. In the case of low altitude application using
UAV, this problem becomes complex issue because the
geometry of images is similarly to close-range photogrammetry.
In the case of standard altitude application of automatic aerial
triangulation, direct geo-referencing approach using GPS and
IMU on UAV is often considered. But, direct geo-referencing
approach using GPS and IMU on Low-cost UAV is difficult in
the case of low altitude application because the GPS
observation is more affected by environment than standard case
of aerial triangulation. Therefore, the automatic detection of

* Corresponding author.
corresponding point between each still image has to be
performed by image based approach. The automatic detection of
corresponding points using coded target is one of the popular
approaches. However, the photogrammetry using Low-cost
UAV is often used under the difficult situation for direct ground
surveying such as disaster area or cultural heritage.
Consequently, only minimum targets can locate in area of
interest, but the correspondence of all images is not provided by
these targets. Another important problem is the robust exterior
orientation using automatic detected corresponding points, GPS
information at waypoints from UAV, minimum ground control
points (GCP). Because the corresponding points from common
feature are often including error and also the positioning
information from Low-cost UAV often includes outlier, robust
exterior orientation has to be investigated.
On the other hand, the authors have been concentrating to
investigate the Structure from Motion (SfM) technique using
both video image and GPS in late years (Anai, 2010). In these
investigations, we have proposed the robust feature point
tracking method based on the “Orientation Code” (OC) image
processing (Ullah 2001). Also, bundle adjustment method for
video image that uses both SfM technique and GPS data with
considering error in GPS observation. If both video image and
still images are obtained from UAV, the tracking information of
video image gives the robust corresponding information
between each still image. From these circumstances mentioned
above, this paper proposes about automatic corresponding point
detection method using both video images and high resolution
still images. Also, the automatic exterior orientation procedure
using corresponding points, GPS and minimum GCP is also