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

• 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
• Institution: Ateneo De Manila University

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...