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.