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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  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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  Can AI Match the Gold Standard? Human Pose Estimation vs Marker-Based Motion Capture2026年7月5日
  Can markerless pose estimation replace marker-based motion capture in sports? Our validation study found a ~10-degree mean joint-angle difference — invisible to the eye, but too much for clinical precision. Here’s what that means.
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  Motion Capture & Performance Analysis (a foundational overview)2026年7月1日
  A foundational overview: marker-based vs markerless pose estimation, the OpenPose/MediaPipe/MeTRAbs coordinate systems, ~10 degree accuracy and why errors happen, kinematics vs kinetics, capture frameworks, and a single-camera to OpenSim example.
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  How To Use OpenPose and OpenCap (free markerless motion capture)2026年7月1日
  A practical getting-started guide to two free markerless motion-capture tools: OpenPose (install the demo, fix the models, run it) and OpenCap (2 iOS cameras, calibration, and 3D capture).
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  The Math Behind Joint Angle Calculation (why atan2 works)2026年7月1日
  The math behind atan2d(det, dot): the determinant is the cross-product magnitude (|a||b|sin), the dot product is |a||b|cos, so their ratio is tan – and why the two-argument atan2 preserves sign and handles angles beyond 90 degrees.

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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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