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A solution to determine the positions of
transportation vehicles without any optical markers
in an area under camera
surveillance was introduced. This solution was based
on a net of cameras on the ceiling of the vehicle
operational areas. A robust
background subtraction method was performed to detect
the contours of all moving objects in every camera
frame. These so called
foreground objects contours were fed into a particle
filter to estimate the position, orientation and
speed of the detected objects over a
certain number of frames. Based on the camera data
this so-called state estimation was performed for all
foreground objects like
humans, other moving obstacles and the vehicles. Due
to the fact that the vehicles can be totally covered
by their payload, they
cannot be detected by color or shape. Instead, the
vehicles were identified by comparing their movement
with the movement of all
detected foreground objects.
transportation vehicles without any optical markers
in an area under camera
surveillance was introduced. This solution was based
on a net of cameras on the ceiling of the vehicle
operational areas. A robust
background subtraction method was performed to detect
the contours of all moving objects in every camera
frame. These so called
foreground objects contours were fed into a particle
filter to estimate the position, orientation and
speed of the detected objects over a
certain number of frames. Based on the camera data
this so-called state estimation was performed for all
foreground objects like
humans, other moving obstacles and the vehicles. Due
to the fact that the vehicles can be totally covered
by their payload, they
cannot be detected by color or shape. Instead, the
vehicles were identified by comparing their movement
with the movement of all
detected foreground objects.