A Simple Approach for Real Time Speed Estimation of On Road Vehicles Using Video Sequences
Mosayebi, A., Khosravi, H. · Transactions on Machine Intelligence · 2021
This paper provides an efficient and simple approach towards real-time speed estimation of on road vehicles for surveillance applications. In the presented method, videos are supposed to be captured with a stationary camera mounted on a two-lane road and there is no need for the camera to be calibrated. The algorithm has two main phases, in the first phase there is an interactive procedure in which lane borders and real world distances are defined just once at the beginning. Then, based on the already received information, two rectangular ROIs are defined for each lane. In the second phase, approximate binary mask of the foreground is created differencing the two consecutive frames. Eventually, calculating centroids and the norm values of the binary mask in the ROIs, algorithm can compute the time that it takes each vehicle to pass between the two aforementioned lines and thus, average speed can be computed. In short, although the algorithm of this paper is simple, it is real-time and efficient, and its implementation doesn’t require any specific hardware. The average error of speed estimation is ±3km/h and the detection accuracy is 83 %.