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 makes 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.