The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B5. Beijing 2008 
automatic procedure because some areas should be removed 
manually, e.g. the vegetated areas where the TLS point 
clouds, from the viewpoint of deformation measurement, are 
particularly noisy. 
c. Matching of the extracted curves. We apply the least squares 
curve matching in order to estimate the transformation (i.e. 
deformation) parameters. 
The above presented approach can be used in two different 
ways. The first one is to check and refine the global matching 
based on surface matching. The second one is to provide good 
initial parameters to the surface matching. In the other side, it is 
worth to underline one of the critical points of the procedure 
which is the extraction of the contours in an automatic way. 
Here below are presented the preliminary test results obtained 
over simulated data in order to check the capability of the 
method and to improve it. Future works will involve the 
validation of the proposed approach using real data. The first 
test was done using a simulated curve, which is shown in Figure 
4. This curve provides good geometric information in all 
directions, i.e. it provides the geometric information needed for 
solving all the transformation parameters. For the test two 
different point clouds, of about 600 points, of the same curve 
have been simulated. Then a Gaussian noise with standard 
deviation of 1 cm has been added to each point cloud. The tests 
consisted in applying a known 6-parameter transformation to 
one of the two curves, and then to estimate the transformation 
parameters by using the curve matching. 
Table 2 shows the results obtained in three different tests. Each 
table represents the mean and the standard deviation of the 
differences between simulated and estimated parameters, which 
were obtained using 30 different simulations. For the first table, 
Tl, the rotation angles have been fixed to zero, i.e. the 
estimated rotations are expected to be zero. The translations in 
X, Y and Z direction ranged randomly between -10 and 10 cm. 
The results of this test show that for the translations there is a 
mean difference up to 3 mm, with a standard deviation of the 
differences of about 1 mm. For the rotations the standard 
deviation of the differences is up to 0.2 gons. 
Z(m) 
Figure 4: Simulated curve for testing and improving the 
implemented curve matching. 
For the second test, whose results are shown in table T2, the 
simulated translations in X, Y and Z ranged between -10 and 10 
cm, and the rotations angles between -10 and 10 gons in each 
direction. The results show again small biases for the 
translations. In X and Z the differences have the same 
magnitude than in the previous. In the Y direction the mean 
difference equals 7 mm. The standard deviation of the 
differences has a noticeable increase, up to 8 mm. A similar 
behaviour can be observed for the rotations. 
Finally the last test, whose results are shown in table T3, has the 
worst results. In this case the simulated translations in X, Y and 
Z ranged between -20 and 20 cm, and the rotations angles 
between -20 and 20 gons in each direction. One may notice that 
the standard deviations of the differences are up to few 
centimetres for the translations, and up to 2.3 gons for rotations. 
These larger values, compared with the previous tables, are 
probably due to the relatively large translation and rotation to 
be estimated. In fact, in all simulations the approximate values 
for the matching were set to zero. 
Tl 
Trans, of 10 cm 
Simulated - Estimated Param. 
(cm) 
(gons) 
Tx Ty Tz 
Rotx 
Roty Rotz 
Mean 
0.2 0.3 0.3 
-0.1 
0.0 -0.2 
Stdv 
0.1 0.1 0.2 
0.2 
0.1 0.0 
T2 
Trans, of 10 cm and Rot. 10 gons 
Simulated - Estimated Param. 
(cm) 
(gons) 
Tx Ty Tz 
Rotx 
Roty Rotz 
Mean 
0.2 0.7 0.3 
-0.3 
0.5 0.4 
Stdv 
0.8 0.6 0.8 
0.4 
0.8 0.7 
T3 
Trans, of 20 cm and Rot. 20 gons 
Simulated - Estimated Param. 
(cm) 
(gons) 
Tx Ty Tz 
Rotx Roty Rotz 
Mean 
0.9 0.1 0.2 
3.2 4.0 3.0 
-0.8 1.2 0.6 
1.2 2.3 1.7 
Stdv 
Table 2: Main statistics of the three tests done in order to 
analyse the capabilities of the curve matching. Tl is related to a 
test where no rotations were simulated. In T2 we added 
rotations between -10 and 10 gons. In T3 the translations vary 
between -10 cm and 10 cm, and the rotations between -20 and 
20 gons. 
5. CONCLUSIONS 
A procedure for deformation measurement using TLS data has 
been presented. The procedure is based on point cloud surface 
matching algorithm described in Gruen and Akca, (2005). In 
addition, the first results obtained with the proposed procedure 
have been presented and a research topic concerning to the 
preliminary results obtained with curve matching have been 
discussed. 
From the results of the validation experiment the following 
aspects have been highlighted: 
• In the 100 m dataset the majority of the targets have errors 
below 1 cm in the three components of the deformation 
vectors. Considering the non optimal characteristics of the 
targets, these represent promising results.