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 | 1 | initial version |
Your clouds look very good!
Regarding the video on the viso2_ros wiki page: The object is at a distance of about 1m and it has a very good texture.
To get the reconstruction, we downsampled the point clouds using VoxelGridFilter and accumulated them in rviz using viso2_ros to generate odometry, setting the fixed frame in rviz to /odom and the decay time of the PointCloud2 display to 10 seconds. You can use fovis_ros for the visual odometry as well. There is no SLAM algorithm in the background so the reconstruction will suffer from drift after a couple of seconds. I don't remember what we got as epipolar error during our calibration. I think 0.25 is okay.
| | 2 | No.2 Revision |
Your clouds look very good!
Regarding the video on the viso2_ros wiki page: The object is at a distance of about 1m and it has a very good texture.
To get the reconstruction, we downsampled the point clouds using VoxelGridFilter and accumulated them in rviz using viso2_ros to generate odometry, setting the fixed frame in rviz to /odom and the decay time of the PointCloud2 display to 10 seconds. You can use fovis_ros for the visual odometry as well. There is no SLAM algorithm in the background so the reconstruction will suffer from drift after a couple of seconds. I don't remember what we got as epipolar error during our calibration. I think 0.25 is okay.
EDIT:
If you want to slow down processing (stereo_image_proc can get quite busy on calculating point clouds) you can throttle one input topic for stereo_image_proc.
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