radarscenes a real world radar point cloud data set for automotive applications

• DOI: 10.5281/zenodo.4559821
• Publication Date: 2021-11-01
• Authors: Jurgen Dickmann; Julius F. Tilly; Markus Hahn; Christian Wöhler; Fabio Weishaupt; Ole Schumann; Nicolas Scheiner
• Keywords: FOS: Computer and information sciences; Computer Science - Machine Learning; 0209 industrial biotechnology; 0202 electrical engineering, electronic engineering, information engineering; 02 engineering and technology; Machine Learning (cs.LG)

A new automotive radar data set with measurements and point-wise annotations from more than four hours of driving is presented. Data provided by four series radar sensors mounted on one test vehicle were recorded and the individual detections of dynamic objects were manually grouped to clusters and labeled afterwards. The purpose of this data set is to enable the development of novel (machine learning-based) radar perception algorithms with the focus on moving road users. Images of the recorded sequences were captured using a documentary camera. For the evaluation of future object detection and classification algorithms, proposals for score calculation are made so that researchers can evaluate their algorithms on a common basis. Additional information as well as download instructions can be found on the website of the data set: www.radar-scenes.com.