Full text: Close-range imaging, long-range vision

D and Woodhouse N., STUDY ON VISUAL TRAVERSE BY LASER SCANNING SENSOR 
ering data sets using an 
ry and machine vision 
ical 3-D Measurement 
Editors), Wichmann, pp 
R.Tanaka, H.Yokoyama, H.Chikatsu 
Tokyo Denki University, Department of Civil Engineering, 
Hatoyama, Saitama, 350-0394, Japan 
(01smg11, yokoyama, chikatsu)@g.dendai.ac.jp 
nd Jones, T. W., 2002. 
r a stretched-lens solar 
Oth International Modal 
fornia, U.S.A. Commission V, WG V/1 
Surface characterisation 
nference on Optical 3-D 
d H. Kahmen (Editors), 
KEY WORDS: Laser scanning, DEM, Three-dimensional, Automatic, Survey 
orammetry at the NASA 
dings, Symposium on 
Jniversity of Melbourne, 
ABSTRACT: 
Recently, ground based laser scanners have been receiving more attention as an useful tool for realtime acquisition of 3D data, and 
its many applications were proposed in various fidds. In particular, scene modelling or visualization of landscape is expected since 
point clouds data are acquired. Generally, total stations are used in topographic surveys, and traverse surveys are popular method as 
topographic surveys. However, only planimetric map is obtained by traverse surveys. Therefore, it is expected 3D traverse surveys 
5. Calibration of CCD 
modes. Conference on 
Sensing '95, SPIE Vol. 
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, P., 2001. Stability and 
ixed wing micro aerial 
{ Atmospheric Flight 
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Eyre J. 1999. Vision 
ualisation in structural 
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which have ability to produce scene model using ground based line laser scanner. 
With these motive, the authors investigated an efficient traverse survey system usng ground based laser scanning sensors, and visual 
traverse system using ground based laser scanning sensor is reported in this paper. 
1. INTRODUCTION 
Regarding topographic surveys, generally total stations are 
used as a popular survey instruments. High accuracy does not 
expected in comparison with total stations. However, ground 
based laser scanners have advantage to acquire 3D data in real 
time, furthermore 3D traverse surveys is expected using laser 
scanners instead of only 2D planimetric map which is obtained 
from popular traverse surveys. 
With this motive, visual traverse system using ground based 
laser scanning sensors is expected. There are some issues, 
however, which resolved before the system may become 
operational. The most bottleneck problem is to reduce noises 
which are caused by trees, grasses, electric poles and so on. 
Many filtering system for noise reduction were proposed in air 
born laser scanning fields (H.Masaharu, 2000, K.Kraus, 2001). 
These noise reduction methods are not so available to ground 
base surveys since ground base surveys are often perform 
limited area where is covered low tress and grasses. 
This paper reports automatic noise reduction method and 
interpolated method for the lack of 3D data, and shows the 
DEM which was acquired 
2. VISUAL TRAVERSE SYSTEM 
Figure 1 shows the flow of visual traverse system. This system 
is consists of some processes. These processes are 
measurement, noise reduction, interpolation, unification of 
coordinates and visualization. Detail procedures for each 
process are descried in afterward. 
  
| Topographic Measurement 
  
    
  
  
| Noise Reduction 
Interpolation 
  
   
  
Unification 
  
Visualization 
  
  
  
Figure 1. Flow of Visual Traverse System 
3. PREMEASURMENT 
3D Laser Scanning Sensor (LD90-3100VHS-FLP, accuracy: 
+25mm) was used in this paper. Distance, vertical angles and 
horizontal angle to the objects, and the intensity for the objects 
are obtained by the laser scanning sensor. The intensity is 
shown the strength of the laser light reflection, and it changes 
by the material of subject, distances to a subject and so on. 
Furthermore, 3D coordinates are calculated using distances and 
posture angles automatically. 
Figure 2 shows sloping ground in the Tokyo Denki University. 
The sloping ground was selected as a test site and was 
measured by following condition. Vertical = 30 deg. (Mark 
Num.: 167 points), Horizontal= 160 deg. (Mark Num.: 878 
points), Composition Num. =150,000 points. Figure 3 shows 
the intensity image. 
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