Multi Vehicle Recognition, Tracking and Counting


Multi Vehicle Recognition, Tracking and Counting



Avinash Beerelli



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


Project Designation

Graduate Research

Primary Advisor

Van Tam Nguyen

Primary Advisor's Department

Computer Science


Stander Symposium project, College of Arts and Sciences

United Nations Sustainable Development Goals

Industry, Innovation, and Infrastructure; Sustainable Cities and Communities

Multi Vehicle Recognition, Tracking and Counting