This paper aims at realizing an automatic parking method through a bird's eye view vision system. With this method, vehicles can make robust and real-time detection and recognition of parking spaces. During parking process, the omnidirectional information of the environment can be obtained by using four on-board fisheye cameras around the vehicle, which are the main part of the bird's eye view vision system. In order to achieve this purpose, a polynomial fisheye distortion model is firstly used for camera calibration. An image mosaicking method based on the Levenberg-Marquardt algorithm is used to combine four individual images from fisheye cameras into one omnidirectional bird's eye view image. Secondly, features of the parking spaces are extracted with a Radon transform based method. Finally, double circular trajectory planning and a preview control strategy are utilized to realize autonomous parking. Through experimental analysis, we can see that the proposed method can get effective and robust real-time results in both parking space recognition and automatic parking.

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