Counting vehicles with cameras

Ciampi L., Amato G., Falchi F., Gennaro C., Rabitti F.

Counting  Deep Learning  Machine Learning  Convolutional Neural Networks 

This paper aims to develop a method that can accurately count vehicles from images of parking areas captured by smart cameras. To this end, we have proposed a deep learning-based approach for car detection that permits the input images to be of arbitrary perspectives, illumination, and occlusions. No other information about the scenes is needed, such as the position of the parking lots or the perspective maps. This solution is tested using Counting CNRPark-EXT, a new dataset created for this specific task and that is another contribution to our research. Our experiments show that our solution outperforms the state-of-the-art approaches.

Source: SEBD 2018 - Italian Symposium on Advanced Database Systems, pp. 1–8, Castellaneta Marina - Taranto - Italy, 24-27/06/2018