talhaahussain/grappling-pose-identification
Third year university dissertation. Continuous Assessment for ECM3401 - Individual Literature Review and Project. Involves the implementation of a human pose estimation computer vision model to detect two combat athletes, and a machine learning algorithm to identify their grappling position.
grappling-pose-identification
Third year university dissertation. Continuous Assessment for ECM3401 - Individual Literature Review and Project. Involves the implementation of a human pose estimation computer vision model to detect two combat athletes, and a machine learning algorithm to identify their grappling position.
Please see specification.pdf for specification.
The literature review (doc/pdf/lit_review.pdf) received a final mark of 74/100. The final report and demo (doc/pdf/final_report.pdf, doc/pdf/final_presentation.pdf) received a final mark of 76/100. The supervisor report for this project gave a mark of 70/100. This work received a final mark of 75/100.
Usage
See src/Pose_Estimation_for_Grappling.ipynb for source code. Google Colab can be used to load the notebook and run the cells. Please run all cells in the order they appear.
Documentation
See doc/pdf/ for all documentation files. For LaTeX generated PDFs, the source can be viewed at doc/TeX/.
Examples
