<div class="csl-bib-body">
<div class="csl-entry">Acharya, D., & Khoshelham, K. (2021). Parking Occupancy Detection and Slot Delineation Using Deep Learning: A Tutorial. In S. Winter & S. Goel (Eds.), <i>Smart Parking in Fast-Growing Cities</i> (pp. 143–173). TU Wien Academic Press. https://doi.org/10.34727/2021/isbn.978-3-85448-045-7_11</div>
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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.
en
dc.language.iso
en
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dc.rights.uri
http://creativecommons.org/licenses/by-sa/4.0/
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dc.subject
automatic parking slot delineation
en
dc.subject
real-time parking occupancy detection
en
dc.subject
CCTV cameras
en
dc.subject
deep learning
en
dc.subject
tutorial
en
dc.title
Parking Occupancy Detection and Slot Delineation Using Deep Learning: A Tutorial
en
dc.type
Book Contribution
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dc.type
Buchbeitrag
de
dc.rights.license
Creative Commons Attribution-ShareAlike 4.0 International
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dc.rights.license
Creative Commons Namensnennung - Weitergabe unter gleichen Bedingungen 4.0 International
de
dc.identifier.doi
10.34727/2021/isbn.978-3-85448-045-7_11
-
dc.contributor.affiliation
Department of Manufacturing, Materials and Mechatronics, RMIT University, Melbourne, Victoria 3000, Australia
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dc.contributor.affiliation
Department of Infrastructure Engineering, The University of Melbourne, Parkville, Victoria 3010, Australia
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dc.contributor.editoraffiliation
TU Wien, Österreich
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dc.contributor.editoraffiliation
Indian Institute of Technology Kanpur, India
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dc.relation.isbn
978-3-85448-045-7
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dc.relation.doi
10.34727/2021/isbn.978-3-85448-045-7
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dc.description.startpage
143
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dc.description.endpage
173
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dc.type.category
Edited Volume Contribution
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tuw.booktitle
Smart Parking in Fast-Growing Cities
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true
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10.34727/2021/isbn.978-3-85448-045-7
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TU Wien Academic Press
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Wien
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tuw.book.chapter
11
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tuw.publication.orgunit
E120 - Department für Geodäsie und Geoinformation
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AC17204939
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dc.description.numberOfPages
31
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0000-0001-6639-1727
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dc.rights.identifier
CC BY-SA 4.0
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dc.rights.identifier
CC BY-SA 4.0
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Open Access
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Publications
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en
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http://purl.org/coar/resource_type/c_3248
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crisitem.author.dept
Department of Manufacturing, Materials and Mechatronics, RMIT University, Melbourne, Victoria 3000, Australia
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crisitem.author.dept
Department of Infrastructure Engineering, The University of Melbourne, Parkville, Victoria 3010, Australia