Field Seeding Algorithm for People Counting Using KINECT Depth Image

In this work, we present a people counting algorithm using depth images acquired from a KINECT camera that is installed vertically, i.e., pointing toward the floor. Our proposed algorithm is referred to as Field seeding algorithm. The key idea is that first a set of local minimum values are detected from several spatially distributed seed locations. Then, the peoplehead blobs are detected from the binary images generated with regard to the threshold values derived from the local minimum values. The recall, accuracy and F-score of our algorithm are comparable to the current state-of-the-art people counting using KINECT, i.e. Water Filling. However, the main advantage over the previous method is that our algorithm operates deterministically, i.e., no any random number generating function is used.