Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/89555
Título: | People tracking in a smart campus context using multiple cameras |
Autor(es): | Matos, Henrique Santos, Henrique |
Palavras-chave: | Multiple Object Tracking Object Detection People Tracking Re-Identification Smart Campus |
Data: | 2023 |
Editora: | CEUR-Ws |
Revista: | CEUR Workshop Proceedings |
Resumo(s): | Object multi-tracking has been a relevant topic for different applications, such as surveillance, mobility, and ambient intelligence. It is particularly challenging when considering open spaces, like Smart Cities, which demand multi-camera solutions with issues like re-identification. In this paper, we describe a framework aiming to provide multi-tracking of people throughout a university campus as part of a larger project (Lab4USpaces) to develop a Smart Campus initiative. Several object detection models and real-time tracking open-source algorithms were compared. The project contemplates a set of low-cost video cameras covering most of the campus, with or without overlapping. After researching different alternatives, the proposed framework uses the YOLOv7 tiny model for object detection, BoT-Sort for multiple object tracking, and Deep Person Reid for re-identification. We also faced challenges concerning the privacy and security of campus users. The multi-tracking system complies with current regulations since no personal identification is ever performed, and no images are stored for longer than necessary for object detection and re-identification. Besides describing the first prototype, this paper discusses some validation tests and describes some potential uses. |
Tipo: | Artigo em ata de conferência |
URI: | https://hdl.handle.net/1822/89555 |
ISSN: | 1613-0073 |
Arbitragem científica: | yes |
Acesso: | Acesso aberto |
Aparece nas coleções: |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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paper_10.pdf | 2,76 MB | Adobe PDF | Ver/Abrir |
Este trabalho está licenciado sob uma Licença Creative Commons