Název:	Autonomous Parking Spot Detection System for Mobile Phones using Drones and Deep Learning
Autoři:	Tirado, Guilleum Budia Semwal, Sudhanshu
Citace zdrojového dokumentu:	WSCG 2021: full papers proceedings: 29. International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision, p. 115-124.
Datum vydání:	2021
Nakladatel:	Václav Skala - UNION Agency
Typ dokumentu:	conferenceObject konferenční příspěvek
URI:	http://hdl.handle.net/11025/45016
ISBN:	978-80-86943-34-3
ISSN:	2464-4617 2464–4625(CD/DVD)
Klíčová slova:	drony;AR;parkoviště;navigace;hluboké učení
Klíčová slova v dalším jazyce:	drones;AR;parking lot;navigation;deep learning
Abstrakt v dalším jazyce:	Many parking lot facilities suffer from capacity over-loads and many times there are no monitoring tools toprovide feedback. As a consequence, the people, want-ing to park, become frustrated as there is considerablyloss of time. In this paper, we present a novel proto-type of an automatic parking-lot analysis platform us-ing image-based machine learning to (a) guide a droneautonomously; and (b) to process useful information tobe handled into a smartphone application to communi-cate with the parking lot users.We have collected a reasonable amount of test imagesto build a classification model using Convolutional neu-ronal networks (CNNs) to classify parking lot images,and build different object detection models to identifyfree and occupied parking spots. Those models havebeen exported to the back-end module of our platformso it can control the drone and record the computed in-formation to its database. In addition, we have imple-mented an iOS application that requests and displaysthe parking lot status and its empty spots.We have been able to prove that this prototype is fea-sible, functional, and opens a path towards future im-provements and refinements. The flight control and thedata classification algorithms have been shown to workusing the machine learning models. In summary, wefound a clear and and concise way to display useful in-formation in real time to our users.
Práva:	© Václav Skala - UNION Agency
Vyskytuje se v kolekcích:	WSCG 2021: Full Papers Proceedings

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