Camera calibration and near-view vehicle speed estimation

In this paper, we present an algorithm of estimating new-view vehicle speed. Different from far-view scenario, near-view image provides more specific vehicle information such as body texture and vehicle identifier which make it practical for individual vehicle speed estimation. The algorithm adopts the idea of Vanishing Point to calibrate camera parameters and Gaussian Mixture Model (GMM) to detect moving vehicles. After calibrating, it transforms image coordinates to the real-world coordinates using a simple model - the Pinhole Model and calculates the vehicle speed in real-world coordinates. Adopting the idea of Vanishing Point, this algorithm only needs two pre-measured parameters: camera height and distance between camera and middle road line, other information such as camera orientation, focal length, and vehicle speed can be extracted from video data.