When I run your open source code(octomapfg method), I get the following result, the point cloud is all white, I don't get the same result as removert, what is the reason?
Thanks for your work. I have no experience using KITTI dataset. It seems the original odometry pose ground truth is for the camera. I wonder if the pose in the pcd is relative to lidar origin? It seems each pcd has been transformed with its pose in its VIEWPOINT field. Looking forward to your reply.
Hi Kin, thank you for your good work!I have a question about groudtruth, that is, how are static points and dynamic points generated in gt? Was it hand-marked?
您好,非常感谢您的工作。但是我使用DUFOMap与Octomap w GF在提供的kitt数据集中取得了较好的结果。但是当我使用自己的数据集时,好像并没有起到作用,车辆产生的动态障碍仍然存在。
可以看到道路中间由于车辆导致的点云仍然存在,我不清楚为何没有起到作用。我保存的每帧点云的方法为:将每帧点云转换到世界坐标系然后保存下来(因为我发现提供的脚本也是这样做的)。但是最后得到的效果十分不好,请问您有什么建议么。
Thanks for the great work! I am evaluating the dynamic object removal using our custom data by a Velodyne HDL 32 (the ground is around -2.2 meters in the LiDAR frame). But the results of dufomap and erasor (use default setting) seem not as good as the KITTI one in the example, can I know if any parameters I can tune? The data includes the pcd and the evaluation output is provided for reference. Thanks a lot!
I am writing to express my sincere gratitude for your open-source contributions. I have encountered an issue during the cmake process and am seeking your assistance. The steps I have taken are as follows: cd methods/octomap && cmake -B build. The output was