Title: Parking Occupancy Detection and Slot Delineation Using Deep Learning: A Tutorial
Authors: Acharya, Debaditya 
Khoshelham, Kourosh  
Editors: Winter, Stephan 
Goel, Salil 
Issue Date: Jul-2021
Book Title: Smart Parking in Fast-Growing Cities 
Abstract: 
This chapter describes a simple method for parking occupancy detection and an automatic parking
slot delineation method using CCTV images. These methods will be presented in the form of MATLAB
tutorials with code snippets to allow the interested reader to implement the method and obtain results
on a sample dataset. The first tutorial will involve fine-tuning a pre-trained deep neural network for
vehicle detection in a sequence of CCTV camera images to determine the occupancy of the parking
spaces. In the second tutorial, we perform spatio-temporal analysis of the detections made by a
state-of-the-art deep learning object detector (Faster-RCNN) for automatic parking slot delineation.
The dataset and the code is made public at https://github.com/DebadityaRMIT/Parking.
Keywords: automatic parking slot delineation; real-time parking occupancy detection; CCTV cameras; deep learning
tutorial
DOI: 10.34727/2021/isbn.978-3-85448-045-7_11
URI: http://hdl.handle.net/20.500.12708/18078
https://doi.org/10.34727/2021/isbn.978-3-85448-045-7_11
Organisation: E120 - Department für Geodäsie und Geoinformation 
License: CC BY-SA 4.0 CC BY-SA 4.0
Publication Type: Book Contribution
Buchbeitrag
Appears in Collections:Book Contribution

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