Fast visual people tracking using a feature-based people detector and thermal imaging

This work presents a tracking system that is tailored towards the needs of small mobile robots. It does not rely on person motion estimation in image space because of unpredictable camera movement while the robot traverses non-flat ground. Additionally it is fast enough to process 5 to 10 frames per second which allows interactive applications. The robustness of the tracking system is improved using fused visible spectrum and thermal images. This reduces false positives and enables the system to work in extreme light conditions. Experiments are conducted on both indoor and outdoor data. Outdoor data was recorded at different temperatures and with a moving robot.