  This paper presents a new approach to accurately track a moving vehicle with
a multiview setup of red-green-blue depth (RGBD) cameras. We first propose a
correction method to eliminate a shift, which occurs in depth sensors when they
become worn. This issue could not be otherwise corrected with the ordinary
calibration procedure. Next, we present a sensor-wise filtering system to
correct for an unknown vehicle motion. A data fusion algorithm is then used to
optimally merge the sensor-wise estimated trajectories. We implement most parts
of our solution in the graphic processor. Hence, the whole system is able to
operate at up to 25 frames per second with a configuration of five cameras.
Test results show the accuracy we achieved and the robustness of our solution
to overcome uncertainties in the measurements and the modelling.
