Error Distribution Simulator · Camera Weighting Factor

Two cameras, one set of crosshair marks. Black = target, red = actual (red arrows show where each mark needs to go). The weighting factor is not "which camera is more accurate" — it is "where the pivot sits, and where the error flows". Alignment works in two steps: first rotate to kill the slope, then translate to zero out the rest — the animation plays them as separate steps.
Scenario: Skewed sheet (rotation fixes it) Keystone distortion (unfixable) 0.00 +0.20
50
Current state:
Set the weighting and errors, then click "▶ Align".

② What the two cameras see (live)

📷 Camera 1 (left marks)—
📷 Camera 2 (right marks)—
On screen the error is magnified 60× to be visible; the numbers here are real millimetres.

③ Axis travel (Step 1 rotate → Step 2 translate)

Y1 (left)
0.00
Y2 (right)
0.00
Translate all
0.00
Y1 and Y2 moving in opposite directions = rotation. At weighting 0, Y1 does not move at all — the pivot is nailed to the left mark. After rotation removes the slope, both sides still share one common offset; Step 2 translates everything to zero it.

④ Result

Left marksRight marks
Before——
Residual after——
Not aligned yet.