New generation autonomous vehicles are expected to successfully navigate in environments with challenging lighting conditions. This is where common, photometric visual perception-based tracking algorithms are put to their limits. We are now exploring the use of radiometric sensors, providing infrared frames (instead of photometric, RGB ones) for object tracking in low-light conditions. The challenge put forward is to develop approaches that can effectively track objects in the dark, in both structured and unstructured environments, including pedestrians, vehicles (cars, trucks, buggies, motorcycles), among others.
The Infrared Tracking Challenge is open to innovators, start-ups, research institutes, and university students from anywhere in the world. Challengers are encouraged to leverage publicly available datasets with similar content as TII's provided sample dataset (labeled) and utilize color-to-thermal domain adaptation techniques in light of scarce publicly available annotated thermal video sequences. Submissions will be evaluated based on criteria set by TII, based on common tracking metrics in the RGB domain.