Biomechanical Golf Swing Analysis using Markerless Three-Dimensional Skeletal Tracking through Truncation-Robust Heatmaps
Name
taylor-bftaylor-sm-sdm-2025-thesis.pdf
Description
Thesis PDF
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21.94 MB
Format
Adobe PDF
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5856640b32227c1280a9ebc989e196d9
Author(s)
Taylor, Benjamin F.
Advisor(s)
Hosoi, Anette "Peko"
Date Issued
May 2025
Publisher
Massachusetts Institute of Technology
Abstract
The efficient generation and transfer of energy in the golf swing has long been a subject of biomechanical interest, with a particular focus on the concept of the kinematic sequence, which is the coordinated segmental rotation of the pelvis, torso, arms, and club. While previous studies have modeled aspects of this sequence using high-end laboratory setups or proprietary systems, few have provided open, quantifiable, and time-resolved measurements of angular kinematics across the full swing cycle. This thesis seeks to address this gap by implementing a markerless temporal skeletal tracking approach built on the open-source MeTRAbs computer vision framework to model and measure joint angles and angular velocities throughout the golf swing. Using two-dimensional video footage of right-handed golfers performing driver swings, the MeTRAbs pose estimation model and supplemental cross-frame temporal motion sequencing code were used to reconstruct three-dimensional joint trajectories and compute rotational kinematics of key body segments.
This study demonstrates the feasibility of using markerless pose estimation to extract golf swing signatures and angular velocity profiles without requiring expensive or inaccessible motion capture equipment. Preliminary analysis suggests that joint coordination patterns and temporal characteristics of body segment angular velocities may reveal quantifiable insights into the kinematic sequence, laying the groundwork for further research and instructional applications. Ultimately, this thesis contributes a replicable and cost-effective framework for analyzing golf swing biomechanics using open-source tools and computer vision.
MIT Department
System Design and Management Program.
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In Copyright - Educational Use Permitted
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