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Design and implementation of an intelligent passenger counting system based on the Kinect sensor

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.