Pauzi, Ainun Syarafana (2025) Enhancing 2D Joints Estimation In Markerless Motion Capture For Improved Tracking Of Spinal Movements. Masters thesis, Universiti Sains Malaysia.
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Abstract
This research aims to improve the anatomical accuracy of 2D human pose estimation models by enhancing the level of detail in the skeletal representation, particularly for the spine region. The research is guided by two main objectives: (1) to identify which of three widely used deep learning models (OpenPose, MediaPipe BlazePose, or MoveNet) most accurately predicts keypoints by comparing model outputs with Inertial Measurement Unit (IMU) data; and (2) to develop a curve-fitting algorithm using Bezier and B-Spline formulas to create realistic spine curvature based on new spine keypoints.
| Item Type: | Thesis (Masters) |
|---|---|
| Subjects: | Q Science > QA Mathematics > QA75.5-76.95 Electronic computers. Computer science |
| Divisions: | Pusat Pengajian Sains Komputer (School of Computer Sciences) > Thesis |
| Depositing User: | Mr Aizat Asmawi Abdul Rahim |
| Date Deposited: | 22 May 2026 07:45 |
| Last Modified: | 22 May 2026 07:45 |
| URI: | http://eprints.usm.my/id/eprint/64267 |
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