i Gn MEME C uL a BESTE
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B3. Istanbul 2004
vehicle candidate. Also this vehicle candidate is fitted by
rectangular polygon fitting algorithms.
Figure 7 example of our algorithm of moving vehicle detection
By using this polygon, correlation of area-based stereo
matching algorithm is calculated to measure degree of same
vehicle matching on different directional TLS images because a
moving vehicle is at different same position on Nadir, Forward
or Backward TLS image. Finally, moving vehicle candidates
with their rectangular polygon and correlation of matching,
which are agreed with moving vehicle model, are detected
moving vehicles.
6. PACKED VEHICLE DETECTION
Parking/Idling Vehicle Detection is our algorithm to
discriminate parked and signals wait vehicle types. From all of
four vertexes of each stopped vehicle polygon to both side of
road edge known from pre-processing stage, on space domain,
perpendicular distances are solved.
Edge Line Equation
0 = AxO+By0+c
IBIE-! meter
Dr» |(Ax*By*C)|(A^2*B^2)^0.5
Stopped Vehicle is parked vehicle if Dr <= Dt |
Figure 8 Concept of Parked Vehicle Detection
At least, one of all vertexes of each stopped vehicle polygon is
agreed with Road . Edge-to-Parked-Vehicle ^ Distance
Thresholding. Road Edge-to-Parked-Vehicle-Distance
Thresholding is defined by the observation of on-street parking
and signals waiting vehicles from the ground true survey.
Figure 9 some result example of Parked/ Idling Vehicle
Classification. Green polygon as Parked Vehicle and Red as
Idling Vehicle
7. SURMERRY
Finally, our contribution presented new algorithms of vehicle
detection by using new aerial image of Three Line Scanner. The
algorithms perform the promising results. The improvement of
algorithms is based on as below;
l. Stopped Vehicle Detection algorithm by using multi TLS
image has been developed.
2. Moving Vehicle Detection algorithms by using multi TLS
image has been created.
3. Parked/ Signals Waiting Vehicle Classification has been
developed.
All of our new proposed vehicle detection algorithms perform
robustness with promising results.
ACKNOWLEGNE
Authors would like to specially thank for STARLABO Co.Ltd
which distribute Three Line Scanner Images and all our
members of Spatial Information Engineering Laboratory,
Centre for Spatial Information Sciences, the University of
Tokyo who encourage and support our works directly and
indirectly.
References
1. Chellappa R., Zheng Q., Davis L., Lin C., Zhang X., and
Rofield A., 1994, Site model based monitoring of aerial
images , Image Understanding Workshop, pp.295-318
Intern
2 Ch
Accur:
(TLS)
Semin
Japan,
lab.g.c
(acces.
3. Hin
[Image
for I
Unvis:
http://
/site. lj
22 Ap:
4. Hi
Vehic!
Techn
Remo
Germe
2004)
5. Na
Mappi
the 2
Noven
http://
ssed 2
6. Shi
from
Remo
7. Son
TLS n
the url
2002,
tokyo.
ccesse
8. Zha
Aerial
http://
(acces