Illumination-invariant road detection and tracking using LWIR polarization characteristics

This paper presents a road detection and tracking technique using polarization characteristics of the road in the long-wave infrared (LWIR) spectrum. Conventional vision-based road detection techniques often apply color and texture information, which tend to underperform in low illumination conditions at night. The Division of Focal Plane (DoFP) infrared polarization imaging technology enables real-time acquisition of polarization characteristics of the road with a monocular camera for day-and-night operation. The polarization characteristics of the road in LWIR embody zero-distribution of Angle of Polarization (AoP) in the road region and the difference of Degree of Polarization (DoP) between the road and vehicles. A road detection and tracking scheme is proposed using the difference in polarization characteristics in LWIR between the road region and the background, along with the intensity and temporal information. We also built a LWIR DoFP Dataset of Road Scene (LDDRS) consisting of a total of 2,113 images annotated manually. Experiments on the LDDRS database demonstrate that the proposed method outperforms two state-of-the-art real-time semantic segmentation networks, FANet-34 and SwiftNet, by 1.4% and 2.1% in terms of IoU, respectively.