Robust Thermal Infrared Pedestrian Detection By Associating Visible Pedestrian Knowledge

Recently, pedestrian detection on thermal infrared images has shown the robust pedestrian detection performance. In this paper, we propose a novel thermal infrared pedestrian detection framework which can associate and utilize the complementary pedestrian knowledge from visible images. Motivated by that humans can associate useful information from other sensors to perform a more reliable decision, we devise a Visible-sensory Pedestrian Associating (VPA) Memory to conduct the robust pedestrian detection by utilizing complementary visible-sensory pedestrian knowledge explicitly. The VPA Memory is trained to store the pedestrian information of visible images and associate it with a given thermal infrared pedestrian knowledge via the memory associating learning. We verify the effectiveness of the proposed framework with extensive experiments, and it achieves state-of-the-art pedestrian detection performance on thermal infrared images.