AI researchers from more than 30 countries around the world came together this week for the AI City Challenge, a competition to spur the development of better machine learning via tasks such as detecting car accidents and tracking a vehicle across a network of cameras. Now in its fourth year, the challenge pushes AI researchers to create more efficient Intelligent Transportation Systems (ITS)…
A team from Carnegie Mellon University won one of the four challenges for tracking a vehicle over a network of multiple cameras. The benchmark data set for this challenge stretches across 46 camera views spanning 16 intersections in Dubuque, Iowa.
In total, the competition drew more than 800 individual researchers on 300 teams from 36 nations; 76 teams submitted code for final review..
Organizers called this year’s AI City Challenge the first to use effectiveness and computation efficiency standards the U.S. Department of Transportation says it needs to consider deployment of this form of automation in the wild.