@InProceedings{SantosBastMaciLima:2020:CoVeHi,
author = "Santos, Adson M. and Bastos-Filho, Carmelo J. A. and Maciel,
Alexandre M. A. and Lima, Estanislau",
affiliation = "{University of Pernambuco} and {University of Pernambuco} and
{University of Pernambuco} and {University of Pernambuco}",
title = "Counting Vehicle with High-Precision in Brazilian Roads Using
YOLOv3 and Deep SORT",
booktitle = "Proceedings...",
year = "2020",
editor = "Musse, Soraia Raupp and Cesar Junior, Roberto Marcondes and
Pelechano, Nuria and Wang, Zhangyang (Atlas)",
organization = "Conference on Graphics, Patterns and Images, 33. (SIBGRAPI)",
publisher = "IEEE Computer Society",
address = "Los Alamitos",
keywords = "Computer Vision, Vehicle Count, Traffic Monitoring System, Object
Detection, Multiple Object Tracking.",
abstract = "The Brazilian National Department of Transport Infrastructure
(DNIT) maintains the National Traffic Counting Plan (PNCT). The
main goal of PNCT is to evaluate the current flow of traffic on
federal highways aiming to define public policies. However, DNIT
still performs the quantitative classificatory surveys not
automated or with invasive equipment. It is crucial for conducting
traffic studies to search for more modern solutions to accomplish
a higher number of automated non-invasive, and low-cost
classificatory surveys. This paper proposes a system that uses
YOLOv3 for object detection and the Deep SORT for multiple objects
tracking algorithms. From the results over real-world videos
collected in Brazilian roads, we obtained a precision above 90% in
the global vehicle count. We also show that our proposal
outperformed other previously proposed tools with 99.15% precision
in public datasets. We believe this paper's proposal allows the
development of a traffic analysis tool to be used for the
automation of the volumetric traffic surveys, enabling to improve
the DNIT agility and generating economy for the public coffers.",
conference-location = "Porto de Galinhas (virtual)",
conference-year = "7-10 Nov. 2020",
doi = "10.1109/SIBGRAPI51738.2020.00018",
url = "http://dx.doi.org/10.1109/SIBGRAPI51738.2020.00018",
language = "en",
ibi = "8JMKD3MGPEW34M/4394BDS",
url = "http://urlib.net/ibi/8JMKD3MGPEW34M/4394BDS",
targetfile = "Article Sibgrapi_2020___Counting Vehicle with
High-Precision_Final_CamaraReady.pdf",
urlaccessdate = "2024, Apr. 29"
}