The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Voi. XXXVII. Part Bl. Beijing 2008 
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Xj = r :j cos Pj cos a,. 
y v = r ij sin Pj cos a,. 
Zy = r tj sin a, 
cc . P 
' is the step angle of the rotating mirror of the 2D laser, J is 
the step rotation angle, i and j are respectively the step number. 
Actually, the portable 3D laser scanner has system errors: (1) 
Installation error /. There is a translational offset / between the 
center of the rotation axis and the center of the mirror wheel of 
the laser scanner. (2) Range error Ap, which results from the 
object’s surface features, air humidity, time-gauges built-in to 
the equipment and the reflected energy, etc. (3) Scan angle 
error (p. When the rotating platform begins to move, it will 
spend some time to reach the constant speed, that results in that 
the of actual reference direction and the axis of coordinates can 
not be are not overlapping, then formula (3) should be 
modified as below: 
position between the 3D range and 2D image sensors sacrifices 
the flexibility of 2D image capture. In fact, because of 
occlusions and self occlusions, the methods above described are 
not suit to the large-scale scenes. We use a hand-held digital 
camera to take the images from different angles, in different 
times, in different focal length. It is a technical challenge 
integrating the images from freely moving cameras with 3D 
models or 3D point clouds. Some related works have done by 
[Stamos I., 2008, Zhao W., 2005.]. I.Stamos’s methods assume 
the existence of at least two vanishing points in the scene and 
register individual 2D images onto a 3D model. W. Zhao’s 
methods align a point cloud computed from the video onto the 
point cloud directly obtained from a 3D sensor. We use W. 
Zhao’s methods to mapping images onto point clouds. 
(1) Recover multi-view relations from an image sequence by 
structure and motion. 
(2) Compute dense depth map using multi-view stereo. 
(3) Determine the camera poses by aligning 3D point clouds 
from the camera and the 3D sensor using ICP (Iterative Closest 
Point). Figure 4 is a result of texture mapping. 
Xj- = (p + Ap) cos a, cos(/?,. + tp) + / cos(/?, + qf) 
(4) 
< y y = (py + Ap) cos a,, sin (ßj +tp) +1 sin (ß } + q>) 
Zy =(py+Ap) since i 
Here, ^ ij , a ‘, are known; ^, 1 and ^ are unknown, so 
the parameters need further calibrated and corrected. 
In order to calibrate the values of ap, l and <p, we select the 
tablet calibration approach. We made 5 tablets, then put two of 
the tablets at the perpendicular direction of x-axis (+, -) of the 
actual reference coordinate system (tablet 1 and tablet 2), 
another two at the perpendicular direction of y-axis (+, -) of the 
actual reference coordinate system (tablet 3 and tablet 4), and 
the last one at the perpendicular direction of z-axis (+) (tablet 5). 
Then, the x-coordinate of the laser point on tablet 1 can be 
known accurately, X=L1. In a similar way, the x-coordinate of 
the laser point on tablet 2 is -L2; the y-coordinate of the laser 
point on tablet 3 is L3; the y-coordinate of the laser point on 
tablet 4 is -L4; the z-coordinate of the laser point on tablet 5 is 
L5. LI to L5 are vertical distances between tablets and the 
origin of the actual reference coordinate. During calibration, we 
moved the tablets to change the values of Ln, so we acquired a 
set of equation, and then we performed a compensating 
computation utilizing additional parameters. After that, we used 
significance test to verify the parameters’ significance, to solve 
correction parameters. 
4. FAST MAPPING IMAGES ONTO POINT CLOUDS 
In practice, the scanned data is not continuous, although 
contains continuous colour information. 2D images mapping on 
3D points is satisfactory for some applications. The traditional 
methods are realized by rigidly attaching a camera onto the 
range scanner and thereby fixing the relative position and 
orientation of the two sensors with respect to each other [Fr'uh 
C., 2003, Sequeira V., 2002, Zhao H.,2003]. Fixing the relative 
Figure 4 3D image of the gate of the university 
Top: 3D reflectance image; Down: 3D colour image. 
5. ANALYSIS OF EXPERIMENTAL RESULTS 
Generally, the quality and accuracy of the recorded 3D points 
of laser scanners are main parameters, which affect on the 
application fields of the laser scanners. Technical data for our 
laser scanner is shown as follows. 
Measurement range 0.5m to 80m 
Accuracy 6mm 
Measurement rate up to 8000/sec 
Laser wavelength near infrared 
Vertical (line) scanning range 0° tol80° 
Horizontal (frame) scanning range 0° to360° 
Weight 6kg 
We did a lot of experiments to test the portable 3D laser scanner 
including data quality, optimal measurement range, influence of 
surface reflectivity, environmental conditions.