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New system estimates athlete's center of mass from phone video

By PulseAugur Editorial · [1 sources] ·

Researchers have developed MuyBridge, a novel on-device system capable of estimating an athlete's center of mass (CoM) trajectory from a single smartphone camera. This system fuses a 2D pose network with a monocular depth network, utilizing anatomical and physical priors to anchor the metric CoM without requiring 3D or task-specific supervision. MuyBridge achieves low error rates on athletic movements and operates at high frame rates, making it suitable for real-time analysis on devices like the iPhone 15. AI

IMPACT Enables real-time biomechanical analysis on mobile devices, potentially aiding athletes and coaches.

RANK_REASON The cluster contains a research paper detailing a new method for human pose estimation. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New system estimates athlete's center of mass from phone video

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The cluster contains a research paper detailing a new method for human pose estimation. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Aidan Bradshaw, Marco Giordano, David Rode, Andreas Habersack, Elif Basokur, Annika Kruse, Markus Tilp, Michele Magno, Peter Wolf, Luca Benini, Christoph Leitner ·

    MuyBridge: Mobile Human Center-of-Mass Estimation from Monocular Video via Sparse Fusion

    arXiv:2609.02854v1 Announce Type: new Abstract: The 3D center of mass (CoM) is a primary quantity in the biomechanical analysis of sport, rehabilitation, and clinical movement, yet existing 3D pose tracking, mesh recovery, and multi-view triangulation methods either optimize 3D k…

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