Multi Vehicle Recognition, Tracking and Counting
Presenter(s)
Avinash Beerelli
Files
Description
Traffic congestion has become a major problem in the cities which are expanding at a rapid rate, making it way for looking at intelligent traffic systems. It is also rising and contributing to issues like wasted fuel, increased cost of transportation, greenhouse gas emissions, and safety as well. There are a number of solutions available which focus on reducing traffic congestion and improve traffic flow by vehicle detection, tracking and counting. In the proposed project we adopt artificial intelligence (AI) algorithms to automatically analyze ongoing traffic condition in real time, detect the vehicles and their classification, such as cars, trucks, buses, or motorbikes. In addition, we are tracking the vehicles along multiple cameras in the city.
Publication Date
4-22-2021
Project Designation
Graduate Research
Primary Advisor
Van Tam Nguyen
Primary Advisor's Department
Computer Science
Keywords
Stander Symposium project, College of Arts and Sciences
United Nations Sustainable Development Goals
Industry, Innovation, and Infrastructure; Sustainable Cities and Communities
Recommended Citation
"Multi Vehicle Recognition, Tracking and Counting" (2021). Stander Symposium Projects. 2145.
https://ecommons.udayton.edu/stander_posters/2145
