Abstract:

This paper proposes a method for fast parking space detection and location based on inverse perspective mapping with binocular cameras. Firstly， the two images captured by binocular camera are projected to the reference plane through back projection to generate two new views， which are called Binocular Inverse Perspective Mapping （BIPM） views. The difference map of the two DBP （BIPM Difference） views can thus be utilized to distinguish objects on the plane or out of the plane. Then， obstacle fast detection is realized by thresholding and filtering the difference map. Meanwhile， the obstacle is localized readily from the reference plane. Compared to the existing methods， the proposed method requires no explicit object detection or 3D reconstruction. It can achieve fast parking space detection and obstacle localization by basic image warping. The proposed method has been verified with actual data collected by the binocular camera of the intelligent vehicle in indoor and outdoor parking lot. The experimental results show that this method can quickly and effectively detect and localize both dynamic and static obstacle objects near the parking space， such as roadblocks， pedestrians， vehicles， ground lockers， etc. The detection speed reaches 18 frames per second （fps）， and the recognition accuracy rate is above 95.0%， outperforming existing methods in terms of algorithm efficiency， accuracy and localization precison.

Key words: autonomous driving, parking space occupation detection, inverse perspective mapping, binocular cameras