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An Efficient YOLOv7x Based Automated Street Parking Space Detection for Smart Cities

Authors:
Tala Bazzaza
Hamid Reza Tohidypour
Yixiao Wang
Panos Nasiopoulos

Keywords: street parking detection; deep learning, YOLOv7; real-time performance; object recognition.

Abstract:
Finding available street parking spots is a cause of increased traffic in metropolitan cities. To address this challenge, in this paper, we propose a unique real-time street parking detection scheme that utilizes visual information and object recognition to accurately detect empty street parking spots. We also introduce a comprehensive video dataset that is captured specifically for this task and is used for training our networks. Among several network options for localization, our tests on YOLOv7 achieved the highest accuracy and speed, making it an ideal choice for real-time street parking detection for human driven as well as autonomous vehicles.

Pages: 37 to 40

Copyright: Copyright (c) IARIA, 2023

Publication date: March 13, 2023

Published in: conference

ISSN: 2327-2058

ISBN: 978-1-68558-061-2

Location: Barcelona, Spain

Dates: from March 13, 2023 to March 17, 2023