Detecting wear and tear in pedestrian crossings using computer vision techniques: approaches, challenges, and opportunities

Rosa, Gonçalo J.M.; Afonso, João M.S.; Gaspar, Pedro Dinis; Soares, V.N.G.J.; Caldeira, J.M.L.P.

Publication

Detecting wear and tear in pedestrian crossings using computer vision techniques: approaches, challenges, and opportunities

2024Journal article

dc.contributor.author	Rosa, Gonçalo J.M.
dc.contributor.author	Afonso, João M.S.
dc.contributor.author	Gaspar, Pedro Dinis
dc.contributor.author	Soares, V.N.G.J.
dc.contributor.author	Caldeira, J.M.L.P.
dc.date.accessioned	2024-03-25T14:11:15Z
dc.date.available	2024-03-25T14:11:15Z
dc.date.issued	2024
dc.description.abstract	Pedestrian crossings are an essential part of the urban landscape, providing safe passage for pedestrians to cross busy streets. While some are regulated by timed signals and are marked with signs and lights, others are simply marked on the road and do not have additional infrastructure. Nevertheless, the markings undergo wear and tear due to traffic, weather, and road maintenance activities. If pedestrian crossing markings are excessively worn, drivers may not be able to see them, which creates road safety issues. This paper presents a study of computer vision techniques that can be used to identify and classify pedestrian crossings. It first introduces the related concepts. Then, it surveys related work and categorizes existing solutions, highlighting their key features, strengths, and limitations. The most promising techniques are identified and described: Convolutional Neural Networks, Histogram of Oriented Gradients, Maximally Stable Extremal Regions, Canny Edge, and thresholding methods. Their performance is evaluated and compared on a custom dataset developed for this work. Insights on open issues and research opportunities in the field are also provided. It is shown that managers responsible for road safety, in the context of a smart city, can benefit from computer vision approaches to automate the process of determining the wear and tear of pedestrian crossings.	pt_PT
dc.description.version	info:eu-repo/semantics/publishedVersion	pt_PT
dc.identifier.citation	ROSA, Gonçalo J.M. [et al.] (2024) - Detecting wear and tear in pedestrian crossings using computer vision techniques: approaches, challenges, and opportunities. Information. Vol. 15:3. DOI: https://doi.org/10.3390/info15030169	pt_PT
dc.identifier.doi	https://doi.org/10.3390/info15030169	pt_PT
dc.identifier.uri	http://hdl.handle.net/10400.11/8944
dc.language.iso	eng	pt_PT
dc.peerreviewed	yes	pt_PT
dc.publisher	MDPI	pt_PT
dc.rights.uri	http://creativecommons.org/licenses/by/4.0/	pt_PT
dc.subject	Pedestrian crossings	pt_PT
dc.subject	Smart cities	pt_PT
dc.subject	Computer vision	pt_PT
dc.subject	State-of-the-art	pt_PT
dc.subject	Performance evaluation	pt_PT
dc.title	Detecting wear and tear in pedestrian crossings using computer vision techniques: approaches, challenges, and opportunities	pt_PT
dc.type	journal article
dspace.entity.type	Publication
oaire.citation.issue	3	pt_PT
oaire.citation.title	Information	pt_PT
oaire.citation.volume	15	pt_PT
person.familyName	Gaspar
person.familyName	Caldeira
person.givenName	Pedro Dinis
person.givenName	João
person.identifier	a4GD8aoAAAAJ
person.identifier.ciencia-id	6111-9F05-2916
person.identifier.ciencia-id	5B19-E130-E382
person.identifier.ciencia-id	A91B-85B8-C27E
person.identifier.orcid	0000-0003-1691-1709
person.identifier.orcid	0000-0002-8057-5474
person.identifier.orcid	0000-0001-5830-3790
person.identifier.rid	N-3016-2013
person.identifier.scopus-author-id	57419570900
person.identifier.scopus-author-id	27067580500
rcaap.rights	openAccess	pt_PT
rcaap.type	article	pt_PT
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