Parking Space Occupancy Verification - Improving Robustness using a Convolutional Neural Network

With the number of privately owned cars increasing, the issue of locating an available parking space becomes apparant. This paper deals with the problem of verifying if a parking space is vacant, using a vision based system overlooking parking areas. In particular the paper proposes a binary classifier system, based on a Convolutional Neural Network, that is capable of determining if a parking space is occupied or not. A benchmark database consisting of images captured from different parking areas, under different weather and illumination conditions, has been used to train and test the system. The system shows promising performance on the database with an overall accuracy of 99.71 %.

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