Considering the complex features of public
places such as mass passenger flow, congestion
and disorder, it is hard to count the number of
passengers precisely. In this paper, a method of
passenger counting system is proposed based on
the range image. This system takes advantage of a
Kinect sensor to acquire the 3D depth information.
First of all, the range image is smoothed with Mean
Shift algorithm to direct every partial pixel toward the
maximal probability density enhanced. Therefore,
the smoothened range image can be better applied
to the subsequent image processing. Secondly, a
classical dynamic threshold segmentation method is
applied to segment the head regions, and the 3D
characteristics of heads are analyzed. They are
differentiated by pixel width, area and circle-like
shape, which efficiently surpass the limits of 2D
images. In addition, the self-adaptive multi-window
tracing method is applied for predicting possible
trajectories, speeds and positions of multi-windows,
in which we establish tracing chains of multiple
targets and lock the tracing targets precisely. This
method proves to be efficient for background noise
removal and environmental disturbance suppression
and can be applied for implementation of the
identifying and counting of heads in public places.
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