Camera-Radar Association for Data Annotation

This paper presents a method to associate detected objects between automotive vision sensors and radar sensors. Recently, studies on classifying objects by combining radar sensors and deep learning have been conducted. However, it is not easy to acquire labeled radar data to train deep learning models. Labeling these training data requires human effort, which is time-consuming. Furthermore, points obtained using radar sensors lack the ability to describe visual features such as the shape of objects, making the labeling process even more challenging. In this paper, we propose a method to annotate radar sensor data by associating the detection result of radar sensor with vision sensor using the iterative closest point algorithm. The proposed method can be used to annotate additional information such as object's class information to radar data without human effort.