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Multi-view pose fusion (Umeyama alignment + visibility-weighted averaging) #355

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@alexarje

Phase-2 follow-up deferred from the sound–motion extension (PRs #351–353): fuse MediaPipe world landmarks from ≥2 uncalibrated camera views via per-frame Umeyama similarity transform on rigid torso landmarks + 2D-visibility-weighted averaging, reporting cross-view residual (mm) as a quality metric. Working reference implementations exist in the Westney study (concert_fuse3d.py / reh_fuse3d.py — byte-identical near-duplicates that should become one library function).

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