Comments (1)
actually you are better off using the theia pose computation for now. For that to work you need theia.
Here is why the standard ceres based method fails:
The theia's pose computation is a 2 step process a) closed form computation of the pose b) non-linear refinement stage.
In my ceres based method, it is only refining the input pose. If the initial estimate of the pose is bad it won't work as expected. This is especially the case under kidnap, when the poses from odometry is really a bad guess for relative pose computation at loop candidates.
I am working to eliminate the dependence on theia. Look at my branch: robust-pose-computation
However it is not ready yet.
Let me know if this answers your question.
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Related Issues (17)
- Keras and TF version HOT 3
- issue in docker HOT 1
- Image channel issues HOT 6
- relocalization error HOT 3
- some problem HOT 5
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- confusing about validation HOT 3
- Run mynteye_vinsfusion.launch error HOT 1
- new branches of robust-pose-computation HOT 2
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