Abstract
This paper presents all-day dataset of paired a multi-spectral 2d vision (RGB-Thermal and RGB stereo) and 3d lidar (Velodyne 32E) data collected in campus and urban environments. Over all days, we successfully captured 50km sequences of synchronized multiple sensors at 25Hz using a fully aligned visible and thermal device, high resolution stereo visible cameras, and high accuracy GPS/IMU inertial navigation system. Therefore, this dataset contains various illumination conditions (day, night, sunset, and sunrise) of multimodal data, which are of particular interest in autonomous driving-assistance tasks such as localization (place recognition, 6D SLAM), moving object detection (pedestrian or car) and scene understanding (drivable region). In this paper, we provide the instruction of our dataset, including a recoding platform, the data format and the software for MATLAB and C++, demonstrating how to load and use the dataset.