Data Fusion and Speed Tagging Alignment Based on Millimeter Wave Radar Detection and Camera Images

A data fusion architecture is proposed for the fusion and speed tagging of the moving object in both camera images and two-dimensional radar detection results. After calibration between the camera and radar coordinate parameters, a Faster-Region Convolutional Neural Network (Faster-RCNN) is used to determine the tagging point of the moving object, while a simplified Recurrent Neural Network (RNN) is used to extract the target trajectory. Experiment results show that the proposed method is able to tag the range speed of moving targets in camera images in a fast and accurate manner.