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The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B3b. Beijing 2008 
modelling scheme for such vehicles is needed to cope with the 
appearance variety. 
For 3D laser data the implicit model can be regarded as 3D 
point pattern (set) of vehicles, whereas the explicit model of the 
vehicle uses the surfaces plus their boundaries or height 
discontinuity as 3D representation. It seems difficult to strictly 
distinguish between two models and to make a choice 
concerning their performance at first glance. Both models focus 
on the geometric features without radiometric properties, and in 
terms of our research objectives and test data characteristics, the 
fundamental and robust features of cars are not always 
summarized by only using the vehicle models due to random 
reflection property of the laser pulse against car surfaces. It 
demands incorporation of more advanced knowledge, such as 
context relations to roads, intensity or global model, into the 
detection strategy. 
\ * » 
i 
s 
. " " 
i 
r fc g , - , , 
* - - 
"* ** J,!’ / »*** «* %. 1». M 
* " * 
b) c) 
Figure 2. Vehicle model (red: ground, green: vehicle) a) 
schematic 3D representation. Measured point cloud in b) side 
view and c) oblique view. 
3.2 Moving vehicle 
The moving vehicle here refers to the instantaneous moving 
cars when the scanning pattern sweeps over them. This category 
comprises the essential part of dynamical information for traffic 
flow analysis while another part of traffic dynamics caused by 
temporally motionless vehicles could not be considered. 
The fundamental difference between scanning and the frame 
camera model, with respect to the moving objects, is the 
presence of motion artifacts in the scanner data (Toth & 
Grejner-Brzezinska, 2006). The frame imagery preserves the 
shape of the moving objects because of the relatively short 
sampling time (camera exposure). But if the relative speed 
between the sensor and the object is significant, the motion 
blurring may increasingly occur. Contrarily, the scanning 
mechanism always produces motion artifacts; moving objects 
will be deformed and have a different shape in the recorded 
data, depending on the relative motion between the sensor and 
the object and sampling frequency. Usually in the laser 
scanning data, the moving object would be projected as 
stretched, compressed or skewed compared to the original one 
and its 2D shape distortion can be summarized in Eq. 1 and 2. In 
order to illustrate this effect we have designed an ALS 
simulator for moving object indication according to sensor 
parameters of riegl laser scanner LMS-Q560. Fig. 3 depicts the 
mutual relationships of moving vehicle under ALS and an 
example in the simulated laser data. 
'v-hl 
|v, | — | v| cos(# v ) 
f < 
a v = arctan 
V 
w v • sin(6* v ) 
IvJ — I v| -cos(0 v ) 
(1) 
(2) 
9 V : angle between the fight path and the vehicle trajectory 
v : vehicle velocity 
v L ’ y ¡-along » v i-aion g '■ l aser scanner velocity and its across- and 
along-track component 
l s : sensed vehicle length; l v : true vehicle length 
w v : true vehicle width 
a v : skewing angle of vehicle form, 90° ±a v = angle of 
parallelogram deformed vehicle shape 
b c 
• ground point 
• point of moving vehicle 
• centroid of vehicle 
outline of vehicle when stationary 
d 
Figure 3. Moving vehicle in the ALS data, a) schematic 
description of mutual relations, b,c) 2D top-view, d) simulated 
laser data 
Generally, a vehicle is assumed to be a rectangle surface in the 
object space. Following conclusions can be obtained from the 
simulation results: the along-track (# v = 07180°) motion leads 
to stretch or shrink of the vehicle length (l s ) in the scanning 
data, whereas the across-track motion {0 v = 90°/270°) leads to