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How to modify parameters when use lidar pointcloud #7
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To test KITTI data by running
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It seems that the frame point cloud is too sparse for FPFH to extract discriminative features. I think you may try some deep-learned methods mentioned in our paper to generate correspondences first, then feed the correspondences to MAC. |
Hello, may I ask how to modify the parameters according to the above operation and test two frames of 16 line LiDAR point clouds? One frame of point cloud has about 50000 points, but the calculation time is very long. Can you give some suggestions on how to modify the parameters。 coefficient computation: 368.68 |
Please follow the above instructions. If the processing time is still significant, increase the parameter of the last line, for example, to 0.999 |
Hello, my problem has been resolved,Thank you very much! |
Thank you for your excellent work! I tried to use this algorithm for lidar point cloud of 16 scans. While I can not get correct transform. Should I modify some parameters for that. The picture is the transform result.
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