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Boxing Punch Detection with Single Static Camera.

Piotr Stefański1, Jan Kozak1, Tomasz Jach1

  • 1Department of Machine Learning, University of Economics in Katowice, 1 Maja 50, 40-287 Katowice, Poland.

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Summary
This summary is machine-generated.

This study introduces a computer vision system for automatic punch detection in Olympic boxing. Using convolutional neural networks and image manipulation, it achieves high accuracy in analyzing boxer performance from single camera footage.

Keywords:
background subtractionboxer detectioncombat sports analysispunch detection

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Area of Science:

  • Sports Analytics
  • Computer Vision
  • Biomechanical Analysis

Background:

  • Player performance monitoring in sports is increasingly leveraging computer vision for its non-invasive nature.
  • Traditional sensor-based systems can interfere with athlete equipment, whereas camera-based approaches offer greater flexibility.
  • Computer vision systems provide valuable insights for coaches, reporters, and audiences in sports like boxing.

Purpose of the Study:

  • To develop and evaluate a system for automatic punch detection in Olympic boxing using a single static camera.
  • To explore image manipulation techniques to enhance the classification performance of the computer vision model.
  • To create a functional system capable of analyzing boxing scenes, identifying boxers, and detecting punches.

Main Methods:

  • Utilizing Euclidean distance to measure the spatial separation between boxers.
  • Employing convolutional neural networks (CNNs) for the classification of boxing footage frames.
  • Implementing and testing three distinct image manipulation strategies to optimize classifier performance prior to training.

Main Results:

  • The proposed system achieved a 95% balanced accuracy in classifying frames.
  • Specific performance metrics include a 49% F1 score for frames containing punches and a 97% accuracy for frames without punches.
  • A working system was developed, demonstrating the ability to mark boxers and label frames with detected actions.

Conclusions:

  • The developed computer vision system effectively detects punches in Olympic boxing with high accuracy.
  • Image manipulation techniques can significantly improve the performance of CNN-based classifiers in sports analytics.
  • The system offers a viable tool for automated performance analysis in boxing, benefiting various stakeholders.