Vehicle Tracking Based on Nonlinear Motion Model

Abstract

How to detect and track vehicle in nonlinear motion is a big problem in computer graphics technology. Monocular vision is complete works like positioning with only one camera; it has a simple structure and a strong applicability. In this paper, we build and solve models of traffic video with nonlinear motion model, to locate and track vehicles in video. We present a new nonlinear movement model using shape model and projection model. The accurately calculated results of position and velocity of the vehicle is given by estimating the vehicle’s speed, posture, the last position. It’s an effective solution to the problem that nonlinear movement is difficult to estimate by KALMAN filter and the tracking process is not stable and reliable enough. The experiments show that the new algorithm has better robustness than EKF and UKF algorithm.