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--- tamiwiki:projects:scanning-tami [2025/04/04 12:48] – wissotsky
+++ tamiwiki:projects:scanning-tami [2025/04/04 18:18] (current) – wissotsky
@@ Line 3: / Line 3: @@
 </WRAP>
-{{tamiwiki:projects:mermaid-diagram-2025-04-03-220229.png}}
+{{tamiwiki:projects:enqvwett3dgqvudxdpmwrsozaihfjyfszimqkpblh0dqy5wdsgwpgmx5jzlhqva_b7ckp2bga2quwfkr3_11i0yqzbjg2slv5bxgz9s3uwbvakx-eecnut0ycxoec2m1s0kv0tdhr79uaj7qhpzn2837ln67eslxckxzwc3rbzaafyc6tjgf0jaorpvpqbf5iixtewrphb1zzmvnyc.svg}}
 <blockquote>
-flowchart TB
 flowchart TB
     subgraph sg1["Global Registration"]
         direction LR
-        fd["Feature Detection"] --> fm["Feature Matching"] --> pte["Pairwise Essential Matrix"] --> pgo["Bundle Adjustment"]
+        vf[(Video Frames)] --> undistort["Undistort Frames"] --> fd
+        fd["Feature Detection"] --> fm
+            subgraph fm["Feature Matching"]
+                direction LR
+                curframe@{ shape: circle, label: "Frame t" }
+                lcpairs[("Loop Closure Groups")]
+                mne["Match to all frames between t-15 and t+15"]
+                islcp{"Is frame in a loop closure group"}
+                mlcp["Match to all frames in the same loop closure group"]
+                findtransitivepairs["Find transitive pairs, If A-B and B-C match, attempt to match A-C"]
+                imgpairs[(Successfully Matched Image Pairs)]
+                curframe --> mne
+                lcpairs -..- islcp
+                mne --> islcp
+                mlcp --> findtransitivepairs
+                islcp --Yes--> mlcp
+                islcp -->|No| findtransitivepairs
+                findtransitivepairs --> imgpairs
+            end
+        imgpairs --> imgpair[("Image pair")]
+            subgraph ComputeEssentialMatrix["Compute Essential Matrix"]
+                direction LR
+                imgpair --> ransacLoop["RANSAC Loop"]
+                subgraph RANSACProcess["RANSAC Process"]
+                    direction LR
+                    ransacLoop --> randomSample["Randomly select 5 point-to-point matches"]
+                    randomSample --> computeE["Compute 10 candidate essential matrices using 5-point algorithm"]
+                    computeE --> countInliers["Count the amount of points where the algebraic epipolar error is lower than a set threshold"]
+                    countInliers --> updateBest["Update best essential matrix if more inliers found in any of the candidates"]
+                    updateBest --> checkIteration{"Max iterations
+                    reached?"}
+                    checkIteration -->|No| ransacLoop
+                end
+                checkIteration -->|Yes| output[("Image Pairs With Estimated Essential Matricies and Keypoint Inlier Masks")]
+            end
+        output --> pgo["Bundle Adjustment"]
     end
     subgraph sg2["Depth Estimation"]
         direction LR
-        pm["Patchmatch"] --RANSAC Polyfit--> nde["Monocular Depth Estimate"] --> gsd["3D Gaussian Splat Depth"] --> kde["KDE Outlier Filtering"]
+        pm["PatchMatch Multi-View Depth Estimation"]
+        nde["DepthAnything v2 Neural Monocular Depth Estimate"]
+        pm & nde --> preprocessing
+        subgraph ConfidenceWeightedDepthCorrection["Confidence-Weighted Depth Map Correction"]
+            direction LR
+            preprocessing["Downscale Neural Estimate to PatchMatch resolution"] --> ransacLoopPolyfit["RANSAC Loop"]
+            subgraph RANSACProcessPolyfit["RANSAC Polynomial Fitting"]
+                ransacLoopPolyfit --> sampleSelection
+                sampleSelection["Random sample selection
+                from depth maps"] --> weightSamples
+                weightSamples["Weight samples by
+                confidence map values"] --> fitModel
+                fitModel["Fit polynomial offset model
+                to weighted samples"] --> evaluateModel
+                evaluateModel["Evaluate model by weighted error"] --> checkConvergence
+                checkConvergence{"Max Iterations Reached?"} -->|No| ransacLoopPolyfit
+                checkConvergence -->|Yes| bestModel["Select best polynomial
+                offset model"]
+            end
+            bestModel --> applyCorrection["Apply polynomial correction to full-res neural depth map"]
+            applyCorrection --> outputPolyfit["Merge Depth and Color into RGBD"]
+        end
+        outputPolyfit --> rgbdpcd["RGBD Point Cloud Projection"] --> gsd["3D Gaussian Splat Training + Depth Rasterization"]
+        gsd --> kde["KDE Outlier Filtering"]
         kde --> storergbd[(RGBD Images)]
     end
@@ Line 28: / Line 105: @@
         storergbd2[(RGBD Images)]
         gpuintgr["GPU VoxelBlockGrid Integration"]
-        isvram{"VRAM Occupation"}
+        isvram{"VRAM Usage"}
         cpuintgr["CPU Uniform Voxel Grid Trilinear Interpolation"]
         exportmesh[(GLTF Mesh)]
-        storergbd2 <==> gpuintgr
+        storergbd2 -.- gpuintgr
         gpuintgr --> isvram
         isvram --Low--> gpuintgr

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