The point cloud co-visibility estimation approach can be further improved by integrating additional sensor modalities, such as inertial measurements, to enhance the robustness of the optimization process. By fusing data from inertial sensors with the existing LiDAR and camera data, the method can benefit from the complementary information provided by inertial measurements, such as acceleration and orientation data. This additional sensor data can help improve the accuracy of estimating the co-visibility of points in the point cloud, especially in dynamic or challenging environments where visual information alone may be insufficient. By incorporating inertial measurements into the optimization process, the method can enhance the reliability and stability of the point cloud colorization by leveraging the rich sensor data from multiple modalities.