A Low-Cost Feature Matching-Based Temporal Registration Method for Radar and Camera

Accurate spatiotemporal registration is essential for effective sensor fusion. However, achieving precise time synchronization at the hardware level is costly. This paper proposes a feature point matching-based temporal registration method to estimate the system's time offset, which is suitable for low-cost radar-vision fusion devices, such as radar-camera systems used in civilian applications. Feature point matching is the key approach for achieving temporal registration between radar and video data. It works by identifying common feature points between radar data and video images to align the timestamps. This method integrates the radar's target detection capability with the imaging ability of visual sensors. It primarily relies on the maximum doppler frequency shift in radar data as feature points, and the pixel peak of the target motion curve in the video image as the corresponding feature points. By matching these feature points, the temporal offset is calibrated. Experimental results show that the estimated time offset is very close to the ground truth, demonstrating that the feature point matching-based method can accurately estimate the time offset and achieve temporal registration between radar and video data.