A high accurate vehicle speed estimation method

Abstract

In this paper, we present a novel approach for accurate vehicle speed estimation from video sequences. Common methods usually track sets of distinguishing features; however, feature extraction is a difficult task in dynamic environments. Herein, we propose a novel analysis method without feature extraction. Initially, a frame difference method is applied to a region of interest, from which projection histograms are obtained and a group of key bins are selected to represent the vehicle motion. Then, all the possible speeds are tested one by one, and the extreme value of the testing function is selected for the corresponding speed. The proposed system was tested on three data sets containing 2054 vehicles, where the ground truth of speed is obtained by a radar speed detector. The experiment results show that the proposed system has an average error of 0.3 km/h, with 99.4% of the estimation speed within the error of range (− 2 km/h, 2 km/h). The system turns out to be robust, accurate and real time for practical use.