"In this paper, we present an algorithm for estimating the occupancy of individual parking spaces. Our method is based on a computer analysis of images obtained by a camera system monitoring the activities on a parking lot. The main idea is to use the a~priori available information about the parking lot geometry and the general shape of common cars to obtain a reliable status of a parking space. We strive to avoid the training phase as much as possible to reduce the time required to bring the system into fully operational state. To achieve this goal, we focus on a probabilistic car model and a physically based feature extraction using computational fluid dynamics. Despite the fact that the very first system of such kind has appeared more than forty years earlier, this area is still an active research topic and a completely satisfactory solution has not been found yet." . "S" . . "Parking lot occupancy detection using computational fluid dynamics"@en . "occupancy detection; parking lot; vision-based surveillance; image analysis"@en . "Fabi\u00E1n, Tom\u00E1\u0161" . "1"^^ . "Proceedings of the 8th International Conference on Computer Recognition Systems CORES 2013" . . "10.1007/978-3-319-00969-8_72" . . . . . "2194-5357" . . "RIV/61989100:27240/13:86088426!RIV14-MSM-27240___" . "CH - \u0160v\u00FDcarsk\u00E1 konfederace" . "Parking lot occupancy detection using computational fluid dynamics" . "226" . . "95395" . "10"^^ . "http://link.springer.com/chapter/10.1007%2F978-3-319-00969-8_72" . . . . "[3ED85669EC76]" . "Parking lot occupancy detection using computational fluid dynamics" . . . "Parking lot occupancy detection using computational fluid dynamics"@en . "27240" . . . "In this paper, we present an algorithm for estimating the occupancy of individual parking spaces. Our method is based on a computer analysis of images obtained by a camera system monitoring the activities on a parking lot. The main idea is to use the a~priori available information about the parking lot geometry and the general shape of common cars to obtain a reliable status of a parking space. We strive to avoid the training phase as much as possible to reduce the time required to bring the system into fully operational state. To achieve this goal, we focus on a probabilistic car model and a physically based feature extraction using computational fluid dynamics. Despite the fact that the very first system of such kind has appeared more than forty years earlier, this area is still an active research topic and a completely satisfactory solution has not been found yet."@en . . "1"^^ . "RIV/61989100:27240/13:86088426" . "2013" .