Hello, thank you very much for providing such great work for the community. I learned a lot from your code.
However, when I tried to evaluate the sequence 00 in the kitti dataset, I can not achieve the same relative translational error. I got 1.12% instead of the reported 0.51% on the README.md page. I save the lidar odometry result and convert it to kitti gt format with the following code:
// read calib
Eigen::Matrix4d Tr;
Eigen::Matrix4d Tr_inv(Eigen::Matrix4d::Identity());
readCalib(calib_file, 0, Tr);
Tr_inv = Tr.inverse();
std::vector<Eigen::Matrix4d, Eigen::aligned_allocator<Eigen::Matrix4d>> lidar_poses;
readTraj(lidar_est_file, lidar_poses);
// transform the lidar traj to cam
std::vector<Eigen::Matrix4f, Eigen::aligned_allocator<Eigen::Matrix4f>> cam_poses;
auto first = Tr * lidar_poses.front().inverse();
for (auto& lidar_pose : lidar_poses) {
auto cam_pose = first * lidar_pose * Tr_inv;
cam_poses.push_back(cam_pose.cast<float>());
}
saveTraj(camera_seq_est_dir + seq + ".txt", cam_poses);
Is there anything wrong I did or do I need to tune some parameters in the system? If so, could you share how you tune the system? Thank you in advance!
Hello, thank you very much for providing such great work for the community. I learned a lot from your code.
However, when I tried to evaluate the sequence 00 in the kitti dataset, I can not achieve the same relative translational error. I got 1.12% instead of the reported 0.51% on the README.md page. I save the lidar odometry result and convert it to kitti gt format with the following code:
Is there anything wrong I did or do I need to tune some parameters in the system? If so, could you share how you tune the system? Thank you in advance!