Visual Parking Space Estimation Using Detection Networks and Rule-Based Systems

In this paper we propose a vision-based two-stage parking detection module. The first stage detects vehicles in images based on a deep neural network. Then, a rule-based system determines the car parking spaces in the image. Experimental results show that our proposed algorithm detects parking space but it also obtains a high false positive rate. We plan to combine visual information with other information fonts to face this drawback.