Master's Thesis on Simultaneous Localization and Mapping in dynamic environments. Separately reconstructs both the static environment and the dynamic objects from it, such as cars.
BSD 3-Clause "New" or "Revised" License
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Evaluate reconstruction on disparity, not depth #26
Comparing reconstructions based on the raw depth is not ideal and can read to problems as disparity goes to zero and Z becomes really noisy, since Z = bf / d.
We should compute disparity (from input, from LIDAR, from raycast) and compare disparities.
This would also allow us to actually use a meaningful unit of measurement instead of just and arbitrary pixel representation of a scaled depth map.
Check out the paper assoc. with the KITTI 2015 stereo bench (Obj SF for autonomous driving, 2015) to see how they evaluate depth. Hint: they care about disparity, NOT the depth.
Comparing reconstructions based on the raw depth is not ideal and can read to problems as disparity goes to zero and Z becomes really noisy, since Z = bf / d.
We should compute disparity (from input, from LIDAR, from raycast) and compare disparities.
This would also allow us to actually use a meaningful unit of measurement instead of just and arbitrary pixel representation of a scaled depth map.
DON'T FORGET TO UPDATE THE DOCS ACCORDINGLY!
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