Spatio-Temporal Optical Flow Analysis for People Counting

In this paper, we present a new approach to count the number of people that cross a counting line from monocular video images. The proposed approach accumulates image slices and estimates the optical flow on them. Then, it performs an online blob detection on these slices in order to extract the crossing persons. The number of persons associated to each blob is determined using a linear regression model applied to blob features which are the position, velocity, orientation and size. The proposed approach is validated on several datasets captured using either a vertical overhead or an oblique mounted camera. The real-time performance and the high counting accuracy of this approach in indoor and outdoor environments are also demonstrated.