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Vizuální systém pro detekci obsazenosti parkoviště pomocí hlubokých neuronových sítí / Visual Car-Detection on the Parking Lots Using Deep Neural Networks

The concept of smart cities is inherently connected with efficient parking solutions based on the knowledge of individual parking space occupancy. The subject of this paper is the design and implementation of a robust system for analyzing parking space occupancy from a multi-camera system with the possibility of visual overlap between cameras. The system is designed and implemented in Robot Operating System (ROS) and its core consists of two separate classifiers. The more successful, however, a slower option is detection by a deep neural network. A quick interaction is provided by a less accurate classifier of movement with a background model. The system is capable of working in real time on a graphic card as well as on a processor. The success rate of the system on a testing data set from real operation exceeds 95 %.

Identiferoai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:363868
Date January 2017
CreatorsStránský, Václav
ContributorsVeľas, Martin, Rozman, Jaroslav
PublisherVysoké učení technické v Brně. Fakulta informačních technologií
Source SetsCzech ETDs
LanguageCzech
Detected LanguageEnglish
Typeinfo:eu-repo/semantics/masterThesis
Rightsinfo:eu-repo/semantics/restrictedAccess

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