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Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/31201
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dc.contributor.authorNascimento dos Santos, AC-
dc.contributor.authorde Paula, K-
dc.contributor.authorVidal, MTL-
dc.contributor.authorda Silva, JMM-
dc.contributor.authorde Sousa, C-
dc.contributor.authorFernandes, LAF-
dc.contributor.authorde Castro, TB-
dc.contributor.authorBedo, M-
dc.contributor.authorKohwalter, TC-
dc.contributor.authorBastos, CAM-
dc.contributor.authorSeixas, FL-
dc.contributor.authorFernandes, NC-
dc.contributor.authorMuchaluat-Saade, DC-
dc.contributor.authorGhinea, G-
dc.coverage.spatialNara, Japan-
dc.date.accessioned2025-05-09T17:01:04Z-
dc.date.available2025-05-09T17:01:04Z-
dc.date.issued2024-11-18-
dc.identifierORCiD: Gheorghita Ghinea https://orcid.org/0000-0003-2578-5580-
dc.identifier.citationNascimento dos Santos, A.C. et al. (2024) 'A Computer Vision Model to Support Individuals with Disabilities Within University Campuses', 2024 IEEE International Conference on E-Health Networking, Application and Services, HealthCom 2024, Nara, Japan, 18-20 November, pp. 1 - 7. doi: 10.1109/HEALTHCOM60970.2024.10880838.en_US
dc.identifier.isbn979-8-3503-5054-8 (ebk)-
dc.identifier.isbn979-8-3503-5055-5 (PoD)-
dc.identifier.urihttps://bura.brunel.ac.uk/handle/2438/31201-
dc.description.abstractThis study introduces MCOF, a multi-camera, computer vision-based system designed to assist visually impaired individuals with mobility on university campuses. The system operates locally and achieves the following performance metrics: (i) detecting body points within 1.2. 10–2seconds, (ii) identifying people, objects, and animals in 2.4. 10–2seconds, and (iii) detecting movements in 5.1. 10−2 seconds. These results were obtained using a GTX 1,660 GPU with up to 6 cameras (or a 6,112MB stream) running concurrently. According to the MCOF architecture, events trigger tickets that are sent to an external information system, which can then implement its own safety and personnel protocols. Additionally, MCOF includes modules to handle electrical and network failures and features an obstruction detection routine for the cameras.en_US
dc.description.sponsorship10.13039/501100002322-Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance.en_US
dc.format.extent1 - 7-
dc.format.mediumPrint-Electronic-
dc.languageEnglish-
dc.language.isoen_USen_US
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.rightsCopyright © 2024 Institute of Electrical and Electronics Engineers (IEEE). Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works ( https://journals.ieeeauthorcenter.ieee.org/become-an-ieee-journal-author/publishing-ethics/guidelines-and-policies/post-publication-policies/ ).-
dc.rights.urihttps://journals.ieeeauthorcenter.ieee.org/become-an-ieee-journal-author/publishing-ethics/guidelines-and-policies/post-publication-policies/-
dc.source25th International Arab Conference on Information Technology (ACIT)-
dc.source25th International Arab Conference on Information Technology (ACIT)-
dc.subjectfall detection-
dc.subjectcomputer vision-
dc.subjecthealthcare-
dc.subjecthuman activity recognization-
dc.subjectcampus safety-
dc.subjectproactive security-
dc.titleA Computer Vision Model to Support Individuals with Disabilities Within University Campusesen_US
dc.typeConference Paperen_US
dc.date.dateAccepted2024-10-18-
dc.identifier.doihttps://doi.org/10.1109/HEALTHCOM60970.2024.10880838-
dc.relation.isPartOf2024 IEEE International Conference on E-Health Networking, Application and Services, HealthCom 2024-
pubs.finish-date2024-11-20-
pubs.finish-date2024-11-20-
pubs.publication-statusPublished-
pubs.start-date2024-11-18-
pubs.start-date2024-11-18-
dcterms.dateAccepted2024-10-18-
dc.rights.holderInstitute of Electrical and Electronics Engineers (IEEE)-
Appears in Collections:Dept of Computer Science Research Papers

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