Fusion of LiDAR and Camera by Scanning in LiDAR Imagery and Image-Guided Diffusion for Urban Road Detection

This paper proposes a new method for road detection based on a 3D LiDAR and a camera. First, the original LiDAR point cloud is re-organized in an ordered way to generate a LiDAR imagery. Then the flat region is extracted from the LiDAR imagery as the candidate road region. Next, a strategy of row- and column- scanning is given in the LiDAR imagery to detect a finer road region from the candidate region. To fuse the point cloud with image information, we transform the point cloud that corresponds to the above detected road region to the image space according to the calibration parameters between the LiDAR and camera. Then we give two image-guided diffusion schemes to conduct image segmentation of road area, respectively. Our experiments demonstrate that this training free approach detects the road region fast, accurately and robustly, and compares favorably with the state-of-the-art on the KITTI benchmark.