Trajectory-Based Scene Description And Classification

Abstract

Video image detection systems (VIDS) provide an opportunity to analyse complex traffic scenes that are captured by stationary video cameras. Our work concentrates on the derivation of traffic relevant parameters from vehicle trajectories. This paper examines different procedures for the description of vehicle trajectories using analytical functions. Derived conical sections (circles, ellipses and hyperboles) as well as straight lines are particularly suitable for this task. Thus, it is possible to describe a suitable trajectory by a maximum of five parameters. A classification algorithm uses these parameters and takes decisions on the turning behaviour of vehicles. A model based approach is following. The a-priori knowledge about the scene (here prejudged and verified vehicle trajectories) is the only required input into this system. One confines himself here to straight lines, circles, ellipses and hyperboles. Other common functions (such as clothoids) are discussed and the choice of the function is being justified.