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--- courses:456:2023:projects:456-2023-12:project-12 [2023/05/11 12:20] – [Influence of Uncertainties in Dense Reconstruction Pipeline] jmangul1
+++ courses:456:2023:projects:456-2023-12:project-12 [2023/05/11 12:40] (current) – [Finalized Approach] jmangul1
@@ Line 98: / Line 98: @@
 In addition to rigid registration methods, the Coherent Point Drift (CPD) reg- istration algorithm was also investigated. CPD is a probabilistic method integrated for rigid and affine point cloud registration between sampled points from the dense reconstruction and CT meshes. This method optimizes regis- tration based on the most likely shape of the DRECO mesh within the CT structure, considering that the computed mesh only represents the section of the sinus anatomy visible in the input video.
+=== Comparison of Registration Types ===
+Table 1 displays the mean errors of the various registration algorithms. Rigid camera pose registration using ICP had the lowest translational error, ranging from 1 to 3mm differences, whereas both Coherent Point Drift algorithms had translational errors on the magnitude of centimeters for the transformed camera poses. All three registration results have significant rotational error, ranging from 12 to 21 degrees. These errors are the same for each type as only the camera position was transformed.
+{{ :courses:456:2023:projects:456-2023-12:table1.png?600 |}}
+//Table 1. Comparison of various registration types using the entire image se- quence (indexes 0 - 1059) and multiple sections for local registration reported as the mean across poses, pixels, and sampled points for camera pose, scale invariant depth, and mesh distance errors, respectively.//
+The CPD rigid and affine registration algorithms have lower errors in the mean distance between meshes but based on visual inspection of the layered meshes and depth renderings, this does not seem to mean that the anatomy is more aligned. The smaller magnitudes may be a result of the intricate sinus anatomy as the closest points between the meshes do not necessarily correspond to the same points within the sinus cavity.
+It is expected that the camera pose + ICP registrations have lower pose errors and the CPD registrations have lower mesh errors because these algorithms com- pute the transformation by minimizing those parameters. The scale invariant depth error serves as a metric independent of the registration. Since the camera pose + ICP registration type had the smallest error in the depth renderings, this algorithm was used to further investigate adjustments to the depth fusion step in the dense reconstruction pipeline.
 ===== Influence of Uncertainties in Dense Reconstruction Pipeline =====

courses/456/2023/projects/456-2023-12/project-12.1683807630.txt.gz · Last modified: 2023/05/11 12:20 by jmangul1