i si
+ : common feature points
: computed still image position
Figure 10. 3D model of First Flight
t : common feature points
-. t computed still image position
Figure 11. Result of Second Flight
i i A
i: common feature points
. : computed still image position
Figure 12. 3D model of Second Flight
From these experiments, it is confirmed that the proposed
automatic corresponding point detection method and robust
exterior orientation method have enough ability for automatic
aerial triangulation using Low-cost UAV in low altitude
photogrammetry.
4. CONCLUSION
In order to perform automatic aerial triangulation using Low-
cost UAV in low altitude application field, we propose
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
automatic corresponding point detection method and robust
exterior orientation method in this investigation.
The automatic corresponding point detection method of this
investigation utilize video image and still image. The video
image can observe the movement of common feature points
continuously by the robust common feature point tracking
method based on OC image processing. Also, the LSM on still
image gives fine accuracy image coordinate. Therefore, the
automatic corresponding point detection method of this
investigation gives many robust corresponding points from
conventional features in each still image automatically.
On the other hand, the proposed exterior orientation procedure
using robust bundle adjustment base on M-estimator have
ability to suppress outlier of GPS observation or miss matched
corresponding points. Therefore, the exterior orientation
parameter and 3D coordinate from this method is obtained in
global coordinate system by using not accurate GPS and
minimum global control points.
However, the estimation of the reliability of proposed method is
still not enough. Also, the process speed of proposed method
has to be more increased. Moreover, in order to perform more
accurate aerial triangulation without using global control points,
utilization of RTK-GPS system has to be considered. Therefore,
our next motivation will be the development of low altitude
automatic aerial triangulation system using UAV that have
RTK-GPS.
REFERENCES
Remondino, F. et. al., 2011. UAV photogrammetry for mapping
and 3D modeling Current status and future perspectives.
International Archives of Photogrammetry, Remote Sensing and
Spatial Information Sciences, Vol. 38(1/C22). ISPRS
Confernce UAV-g, Zurich, Switzerland
T, Anai, N. Fukaya, et. al. 2010. Application of Orientation
Code Matching for Structure from Motion. Proceedings of the
ISPRS Commission V Mid-Term Symposium. Vol XXXVIII,
Part 5. pp33-38
D, G, Lowe. 2004. Distinctive image features from scale-
invariant keypoints. International Journal of Computer Vision,
60(2). pp91-110
H. Bay, Andreas Ess, Tinne Tuytelaars, Luc Van Gool, 2008.
SURF: Speeded Up Robust Features, Computer Vision and
Image Understanding (CVIU), Vol. 110, No. 3, pp. 346--359