irt BS. Istanbul 2004 
ferences. It can be 
in of simulated data 
membered that the 
)n were not entirely 
  
———Ü——— 
7 
© 
v 
/ 
À 
= 
vd 
75 
T 3 | 
^ c 
~~ = 
A 
MÀ 
'es respect to object 
ata cannot be treated 
ive depiction of how 
et is, or is not, with 
8. For this represen- 
ine segments inside 
sponding lengths of 
| respect to nominal 
8 the second order 
f differences respect 
nces in length is pre- 
ir from origin. More 
origin, more inaccu- 
| on this assumption 
nent is, more prob- 
ts will locate farther 
r lines is larger than 
sential to notice that 
nce is below 10mm 
ble consistency with 
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part BS. Istanbul 2004 
  
  
  
nt pairwise. The dif- 
f line segments. 
5 CONCLUSIONS 
In this paper the refined mathematical model has been re- 
presented, which also encompasses possible deviation from 
the ideal model of imaging in practice. Also self-calibration 
technique has been applied in the estimation model on the 
final stage. Acquiring initial values for parameters is quite 
a straight forward procedure, which can partly be comput- 
erized with simple instrumentation. Some attention has 
to be paid to their correctness though. The method has 
been tested in real close-range measuring conditions with- 
out any optimization. Despite some unreliability in the ref- 
erence data the accuracy with this method can be estimated 
to be better or at least the same as with equivalent stereo 
pair measurements. When the object space to be measured 
is up to 20 — 30m the achieved accuracy of 0.01 — 0.02m 
is quite adequate for large variety of applications. 
However, in order to reveal the real power of this method, 
further research work has to be done and more specific tests 
have to be arranged where imaging and measuring con- 
ditions are not the limiting factors. The presented method 
is designed to be used for measuring surrounding object 
space from the single point of location. However, more 
than one such camera stations can be combined to achieve 
more precise and geometrically improved constellation in 
terms of measuring accuracy. 
REFERENCES 
Fraser, C., 1989. Optimatization of networks in non- 
topographic photogrammetry. ASPRS, Falls Church, Vir- 
ginia U.S.A., pp. 95-106. 
Heikkinen, J., 1998. Video based 3d modeling. In: Real- 
Time Imaging and Dynamic Analysis, Vol. XX XII, Part 5, 
ISPRS, Hakodate, Japan, pp. 712-716. 
Heikkinen, J., 2000. Circular image block measurements. 
In: XIX ISPRS Congress, Vol. XXXIII Part B5/1, ISPRS, 
Amsterdam, Netherlands, pp. 358—365. 
Heikkinen, J., 2001. Video measurements for forest inven- 
tory. In: S. E. Hakim and A. Grün (eds), Videometrics and 
Optical Methods for 3D Shape Measurements, Vol. 4309, 
SPIE, San Jose,CA U.S.A., pp. 93-100. 
Heikkinen, J., 2002. Performance of circular image blocks 
in close-range photogrammetry. In: Close-Range Imaging, 
Long-Range Vision, Vol. XXXIV Part 5, ISPRS, Corfu, 
Greece, pp. 39-41. 
Parian, A. J. and Grün, A., 2004. A refined sensor model 
for panoramic cameras. In: H.-G. Maas and D. Schnei- 
der (eds), Panoramic Photogrammetry Workshop, Vol. 
XXXIV Part 5/W16, ISPRS, Dresden, Germany.