The dataset contains 21 full-HD videos, each around 1 hr long, captured at six different locations. Vehicles in the videos (20 865 instances in total) are annotated with the precise speed measurements from optical gates using LiDAR and verified with several reference GPS tracks. The dataset is available for download and it contains the videos and metadata (calibration, lengths of features in image, annotations, and so on) for future comparison and evaluation. This dataset was published with paper SOCHOR Jakub et al. Comprehensive Data Set for Automatic Single Camera Visual Speed Measurement, IEEE T-ITS.

The dataset has been generated using Town 1 and Town 2 of CARLA Simulator. The dataset consists of 50 camera configurations with each town having 25 configurations. The parameters modified for generating the configurations include f ov, x, y, z, pitch, yaw, and roll. Here, f ov is the field of view, (x, y, z) is the translation while (pitch, yaw, and roll) is the rotation between the cameras. The total number of image pairs is 1,23,017, out of which 58,596 belong to Town 1 while 64,421 belong to Town 2, the difference in the number of images is due to the length of the tracks.

Description OV dataset is the camera calibration dataset. There are 16 lenses ranging from 90° to 180° FOV: * 2012-A0 (single-plane target) * 3136-H0 (single-plane target) * 5501-C4 (single-plane target) * 130108MP (single-plane target) * ov00—ov07 (corner target) * ov00—ov03 (cube target) Note: We also provide the other datasets evaluated in the BabelCalib paper: Kalibr, OCamCalib and UZH. # Format The datasets have a Deltille format. The Deltille detector is a robust deltille and checkerboard detector. It comes with detector library, example detector code, and MATLAB bindings. BabelCalib provides functions for calibration and evaluation using the Deltille software's outputs. Calibration from Deltille detections requires format conversion which is peformed by import_ODT. Please see a complete calibration example from Deltille data.