A Computer Vision Model to Support Individuals with Disabilities Within University Campuses
This 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<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−2</sup> 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.
Authors
- Leandro A. F. Fernandes (ORCID: https://orcid.org/0000-0001-8491-793X)
- Flávio Luiz Seixas (ORCID: https://orcid.org/0000-0002-7160-0818)
- Débora C. Muchaluat-Saade (ORCID: https://orcid.org/0000-0002-1233-9736)
- Carlos Alberto Malcher Bastos
- Allan Costa Nascimento dos Santos (ORCID: https://orcid.org/0000-0002-9400-5990)
- Marcos Bedo (ORCID: https://orcid.org/0000-0003-2198-4670)
- Marcos Vidal (ORCID: https://orcid.org/0000-0001-5042-3480)
- Natália C. Fernandes (ORCID: https://orcid.org/0000-0001-9481-6374)
- Gheorghiță Ghinea (ORCID: https://orcid.org/0000-0003-2578-5580)
- Troy Kohwalter (ORCID: https://orcid.org/0000-0002-5183-473X)
- Carla Sousa (ORCID: https://orcid.org/0000-0003-2313-0775)
- Tiago Castro
- JÉSSICA MACHADO FELIPE DA SILVA (ORCID: https://orcid.org/0009-0004-0952-8386)
- Karina de Paula
Institutions
- Universidade Federal Fluminense (BR)
- Brunel University of London (GB)
Publication Details
- Published
- 2024-11-18
- DOI
- https://doi.org/10.1109/healthcom60970.2024.10880838
- Citations
- 3
- Primary Topic
- Subtitles and Audiovisual Media
- Type
- article
- Field-Weighted Citation Impact
- 8.34
Funders
- Coordenação de Aperfeiçoamento de Pessoal de Nível Superior