Vehicle Speed Detection Using Open CV

Video and image processing has been used for traffic surveillance, analysis and monitoring of traffic conditions in many cities and urban areas. This paper aims to present another approach to estimate the vehicles velocity. In this study, the captured traffic movies are collected with a stationary camera which is mounted on a freeway. The camera was calibrated based on geometrical equations that were supported directly by using references. Camera calibration for exact measurements may be possible while accurate speed estimation can still be quite difficult to achieve. The designed system has the ability to be extended to another related traffic application. The average error of the detected vehicle speed was ± 7 km/h and the experiment was operated at different resolutions and different video sequences. The rapid recent advancements in the computation ability of everyday computers have made it possible to widely apply deep learning methods to the analysis of traffic surveillance videos. Traffic flow prediction, anomaly detection, vehicle re-identification, and vehicle tracking are basic components in traffic analysis. Among these applications, traffic flow prediction, or vehicle speed estimation, is one of the most important research topics of recent years. Good solutions to this problem could prevent traffic collisions and help improve road planning by better estimating transit demand. We combine modern deep learning models with classic computer vision approaches to propose an efficient way to predict vehicle speed. In this paper, we introduce some state-of-the-art approaches in vehicle speed estimation, vehicle detection, and object tracking. Optical flow includes the information on the speed and direction of pixel motion in an image. Third, we construct a multi-scale convolutional network. This network extracts information on various characteristics of vehicles in motion.

Keywords: Vehicle speed detection, video sequence, computer vision, background modelling, traffic monitoring, OpenCV