Pedestrian detection system in low illumination conditions through Fusion of image and range data

Abstract

The development of pedestrian detection techniques mainly focused on the research on suitable visual feature in the past decades. However, illumination is not only important to human visual ability to view the surroundings, but is also very critical to the choice of visual features in the vision-based detection methods. Since the visual information can be greatly affected by different illuminations, the resulting detection methods can produce unreliable results. Image-Range Fusion System (IRFS) is proposed by applying the image data from a camera and the range data from a radar simultaneously. For the image part, Logarithm Weighted Pattern (LWP) and a Dynamically Illuminated Object (DIO) detector is proposed to overcome the possible problem caused by the uncertain partial lighting condition within a low-illumination environment. To validate our results, several experiments have been conducted, and the overall system performance is shown to be 88.69%/82.81% of recall/ precision under real-time computing setting.