People Counting based on Kinect Depth Data

The people’s counting is one of the most important parts in the design of any system for behavioral analysis. It is used to measure and manage people’s flow within zones with restricted attendance. In this work, we propose a counting strategy for counting the number of people entering and leaving a given closed area. Our counting method is based on the use of depth map obtained from a Kinect sensor installed in a zenithal position with respect to the motion direction. It is used to count the number of people crossing a virtual line of interest (LOI). The proposed method is based on the use of two main modules a people detection module that is used to detect individuals crossing the LOI and a tracking module that is used to track detected individuals to determine the direction of their motions. The people detection is based on the design of a smart sensor that is used with both the grayscale image that represents depth changes and the binary image that represents foreground objects within the depth map to detect and localize individuals. Then, these individuals are tracked by the second module to determine the direction of their motions.