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International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B5. Istanbul 2004
But there is every possibility of extracting using by 3D shape
and texture information. As a feature, various features have to
be attempted to extract. Also, application to use this detailed
extraction has to be considered such as earthquake disaster,
volcanic eruption, urban mapping, etc.
Detected Feature Distinctive Feature
Concrete Ground - ground surface
Surface. - gray color (concrete color)
Grass Ground - ground surface
Surface - green color (vegetation color)
Scatter Point
not green color (not vegetation)
Artificial Shape
Manmade object
(complex shape)
Manmade object
(Box shape) - not green color (not vegetation)
Natural vegetation | - Scatter Point
not green color (not vegetation)
Vertical Plane
gray color
Wall
Table 5. Extracted Features
5. CONCLUSION
In conclusion, all the sensors, laser scanner, digital camera and
IMU, GPS are integrated to construct digital surface model.
Calibration of laser scanner and digital camera is conducted to
know relative position and attitude of each sensor against IMU.
This rigorous geometric relationship is used for constructing
DSM and integrating digital camera images. In this paper, we
propose a new method of direct geo-referencing by the
combination of bundle block adjustment and Kalman filter.
Because of the aiding Kalman filter by bundle block
adjustment, geo-referenced range data and CCD images are
overlap correctly. Feature extraction. from range data and
image data is more effective than feature extraction from image
data alone.
In this paper, all the sensors and equipments are assembled on
a unmanned helicopter. This paper focus on how integrate
these sensors with mobile platform.
6. REFERENCES
Nagai, M., Shibasaki, R., Zhao, H., Manandhar D., 2003.
Development of Digital Surface Model and Feature
Extraction by Integrating Laser Scanner and CCD sensor,
Proceedings of the 24th Asian Conference on Remote
Sensing, 3-7, Busan, Korea.
Kumagai, H., Kubo, Y., Kihara, M., and Sugimoto, S.,
2002. DGPS/INS/VMS Integration for High Accuracy
Land-Vehicle Positioning, Journal of the Japan society of
Photogrammetry and Remote Sensing, vol4l no.4
pp.77-84
Kuamgai, H., Kindo, T., Kubo, Y., Sugimoto, S., 2000.
DGPS/INS/VMS Integration for High Accuracy Land-
Vehicle Positioning, Proceedings of the Institute of
Navigation ION GPS-2000, Salt Lake.
Manandhar, D., Shibasaki, R., 2002. Auto-Extraction of
Urban Features from Vehicle-Borne Laser Data,
ISPRS "GeoSpatial Theory, Processing and Application ",
Ottawa.
Zhao, H., Shibasaki, R., 2000. Reconstruction of
Textured Urban 3D Model by Ground-Based Laser
Range and CCD Images, [EICE Trans. Inf &Syst.,
vol.E83-D, No.7.
Zhao, H., Shibasaki, R., 2001. High Accurate Positioning
and Mapping in Urban Area using Laser Range Scanner,
Proceedings of IEEE Intelligent Vehicles Symposium,
Tokyo.
7. ACKNOWLEDGEMENT
We would like to express highly appreciation to Dr. Hideo
Kumagai, Tamagawaseiki co.ltd. He provides the IMU for this
research and his guidance for IMU data processing lead this
research to success.