Add Essential Matrix Optimization #816
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Very promising results on South Building Without E Optimization
With E Optimization
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Better results across the board
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among non-rc3 medium sized datasets, it seems clearly better for south building, but worse for gerrard hall and palace of fine arts. we should focus on these medium sized and other non-CI large datasets. |
| # Create GTSAM objects. | ||
| graph = gtsam.NonlinearFactorGraph() | ||
| initial = gtsam.Values() | ||
| noise_model=gtsam.noiseModel.Isotropic.Sigma(1, 1e-2) |
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probably is too high, considering this is used on calibrated keypoints?
| # pre_ba_i2Ui1, | ||
| # i2Ti1_prior, | ||
| # ) | ||
| post_ba_i2Ri1, post_ba_i2Ui1 = optimize_essential_matrix( |
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maybe use an option to enable this? you could do:
if len(pre_ba_v_corr_idxs) >= self.processor._min_num_inliers_est_model:
if self._bundle_adjust:
...
elif self._optimize_essential_matrix:
...
| initial.insert(0, gtsam.EssentialMatrix(i2Ri1, i2Ui1)) | ||
| for kp1, kp2 in zip(mkps1, mkps2): | ||
| graph.add( | ||
| gtsam.EssentialMatrixFactor( |
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we should probably use the newer implementations @dellaert added. I think some bugs with the essential matrix were fixed too?
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Add essential matrix optimization similar to what's presented in this paper: https://openaccess.thecvf.com/content_iccv_2015/papers/Sweeney_Optimizing_the_Viewing_ICCV_2015_paper.pdf.
This is what's also used by GLOMAP. Some things to think about: