Accurate Estimation of Wheel Center Points for Estimate of Vehicle Baseline Length in a Circular Fisheye Image

Vehicle classification is very important in traffic flow analysis for traffic monitoring systems. Accurate estimation of wheel baseline length can provide a useful cue for vehicle classification. In this paper, we propose a new method for detecting accurate wheel center points and estimating the wheel baseline length of a vehicle taking the distortion in the circular fisheye images into consideration. Our proposed method consists of two steps, considering distortional shape of the wheel in a circular fisheye image. At the first step, tire-road contact points are roughly detected based on the centroid of wheel region. At the second step, the wheel area is calculated based on detected contact points, and the wheel´s center points are accurately detected by position matching of wheel area. And it is confirmed that the proposed method is effective in circular fisheye image by experimental results.