Human Pose Estimation Research & Development

From sports & exercise science to AI. I build markerless human pose estimation and AI-driven movement analysis — and break down the research here and on YouTube.

Focus areas

Latest articles

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  Does Jump Strength Predict Kick Speed? The Support-Leg Secret in Soccer2026年7月8日
  Does single-leg jump strength predict soccer kick speed? In 6 amateur players, the dominant leg kicked harder (99 vs 85 km/h) — but the real surprise was that a stronger non-dominant support leg went with a faster dominant-leg kick.
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  How Accurate Is ARKit for Motion Capture? I Measured It Across 10 Exercises2026年7月8日
  Apple’s ARKit turns an iPhone into a markerless 3D motion tracker — but how accurate is it? I tested it across 10 exercises with 11 participants. Single joints at peak flexion were within ~3°, but errors near full extension and the floor reached up to 63°.
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  5 Apps That Put Motion Capture in Your Pocket — Do They Work?2026年7月8日
  Can a smartphone app really measure how you move? Five motion-capture apps — ViMAS, KinesioCapture, Coach’s Eye, LGait, and SmartGait — have been validated against VICON and 3D systems. Here’s the accuracy each study actually found, app by app.
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  Can Your Phone Fix Your Form? 3D Motion Capture with ARKit2026年7月8日
  Can your phone measure how you move accurately enough to fix your form? Here’s why Apple’s ARKit — 3D motion capture from ordinary 2D video, auto-calibrated and real-time — is a promising answer, and how it compares with VICON, 2D video, and Kinect.
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  3D Markerless Motion Capture: Which Setup? 3 Approaches Compared2026年7月6日
  Three ways to capture 3D movement without markers — single-camera AI depth, a depth sensor, or multiple cameras. Here’s how they compare on accuracy, cost, and setup, and how to choose.
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  Which Pose-Estimation Model Is Most Accurate? 6 Models vs the Gold Standard (VICON)2026年7月5日
  We benchmarked pose estimation accuracy across six models — MediaPipe, MeTRAbs, YOLO and MoveNet — against the VICON gold standard. Two clear tiers emerged; here’s which to use, and when.

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Profile

I’m Takashi Fukushima, a researcher and developer working across sports & exercise science, motion capture, and computer vision. My focus is markerless human pose estimation and AI-driven movement analysis, alongside XR development with Unity and Meta Quest. I publish peer-reviewed research and break it down here and on my channel.

• Human Pose Estimation (MediaPipe, OpenPose, latest methods)
• Motion Capture & Sports Biomechanics
• Computer Vision & AI movement analysis
• XR / Metaverse development (Unity & Meta Quest)

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