Fusion and Visualization of Three-Dimensional Point Cloud and Optical Images

Due to the lack of color information of three-dimensional point cloud and spatial information of optical images, a fusion method based on lidar and camera automatic calibration is proposed in this work. The fused data contains both the spatial information of the point cloud and color texture information of the optical images. First, the planar calibration plate was used to automatically calibrate the lidar and optical camera in steps. Second, the coordinate relationship was established through a collinear equation, and the color texture information of the optical image is given to the point cloud for fusion and visualization. The experimental results show that the fusion accuracy and the level of automation of the proposed method are improved. Compared to the calibration fusion method based on manual matching, the accuracy of the proposed method is improved by 51. 7%. Compared to the calibration fusion method based on a trapezoidal checkerboard calibration board, the accuracy of the proposed method is improved by 36. 4%. Considering the visualization results from multiple angles, the proposed method can better restore the color and spatial effects of real scenes.