Resumen
To achieve significant improvements in public transport it is necessary to develop an autonomous system that locates and counts passengers in real time in scenarios with a high level of occlusion, providing tools to efficiently solve problems such as reduction and stabilization in travel times, greater fluency, better control of fleets and less congestion. A deep learning method based in transfer learning is used to accomplish this: You Only Look Once (YOLO) version 3 and Faster RCNN Inception version 2 architectures are fine tuned using PAMELA-UANDES dataset, which contains annotated images of the boarding and alighting of passengers on a subway platform from a superior perspective. The locations given by the detector are passed through a multiple object tracking system implemented based on a Markov decision process that associates subjects in consecutive frames and assigns identities considering overlaps between past detections and predicted positions using a Kalman filter.
Idioma original | Inglés |
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Páginas | 231-238 |
Número de páginas | 8 |
DOI | |
Estado | Publicada - 7 oct. 2021 |
Evento | 11th International Conference of Pattern Recognition Systems, ICPRS 2021 - Virtual, Online Duración: 17 mar. 2021 → 19 mar. 2021 |
Conferencia
Conferencia | 11th International Conference of Pattern Recognition Systems, ICPRS 2021 |
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Ciudad | Virtual, Online |
Período | 17/03/21 → 19/03/21 |
Nota bibliográfica
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