Autonomous parking is one of the primary functionalities of intelligent vehicles. This requires the accurate detection of a free parking slot and its dimensions. Here we propose a method using a novel combination of computer vision techniques on the camera data mounted on sides of a car. Our occupancy check method is based on perspectivity guided motion segmentation, which makes it a generic approach for handling random obstacles without prior knowledge. When tested on our dataset collected in environments such as shadows, wet surface, indoors and outdoors with obstacles including cars, motorbikes, cones, carton boxes and trees, this method achieved a promising performance with F1 score higher than 97%. With the ability to run on low computational devices such as CPU, this method is adaptable to practical solutions for both AD and aftermarket ADAS systems.

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