Vehicle Detection Using YOLO and Mobility Tracking During COVID-19 Pandemic Lockdowns

Vehicle Detection Using YOLO and Mobility Tracking During COVID-19 Pandemic Lockdowns

Data-driven approaches to traffic monitoring have important applications in tracking vehicle mobility in the COVID-19 pandemic lockdowns. We report preliminary results of a pipeline that uses the You Only Look Once (YOLOv3) and the Simple Online and Realtime Tracking (SORT) algorithms to count and c...

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Bibliographic Details
Main Authors: Tan, Marion Ivan L, Calgo, Clyde J, Cabantac, Sheanne Eric P, Honrado, Jaime Luis E, Libatique, Nathaniel Joseph C, Tangonan, Gregory L
Format: text
Published: Archīum Ateneo 2021
Subjects:
COVID-19
Pandemics
Vehicle detection
Conferences
Pipelines
Internet
Classification algorithms
traffic videos
object detection
COVID-19 pandemic
SARS-COV-2
lockdown
community mobility
Electrical and Computer Engineering
Transportation
Online Access:https://archium.ateneo.edu/ecce-faculty-pubs/120
https://ieeexplore.ieee.org/document/9612481
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Institution: Ateneo De Manila University

Internet

https://archium.ateneo.edu/ecce-faculty-pubs/120
https://ieeexplore.ieee.org/document/9612481

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