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Application of video image processing in sports action recognition based on particle swarm optimization algorithm.

Youming Zhang¹, Xingchen Hou¹

¹School of Physical Education and Health Science, Mudanjiang Normal University, Mudanjiang 157011, China.

Preventive Medicine

|June 28, 2023

Summary

This study introduces a novel sports training system using particle swarm optimization and video image processing for enhanced human motion recognition. The system effectively analyzes athlete movements, offering a more intuitive way to identify shortcomings and improve training outcomes.

Keywords:

Action recognition Particle swarm optimization algorithm Physical education teaching Video image processing

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Area of Science:

Sports Science
Computer Vision
Optimization Algorithms

Background:

Traditional sports training relies on subjective coach observation, limiting efficiency and athlete development.
Existing methods lack objective, data-driven analysis of athletic movements.
There is a need for advanced technologies to enhance sports training methodologies.

Purpose of the Study:

To develop and evaluate a human motion recognition system for sports training.
To integrate particle swarm optimization (PSO) with video image processing for improved sports analysis.
To provide athletes with an intuitive tool for self-assessment and performance enhancement.

Main Methods:

Video image processing techniques including decoding, noise removal, and enhancement.
Establishing a manikin structure for key point collection from video data.
Applying the particle swarm optimization algorithm to motion recognition and data analysis.

Main Results:

The developed system effectively detects changes in athlete sampling point paths.
The system allows for objective comparison of athlete movements against standard benchmarks.
Demonstrated a significant auxiliary role in identifying training deficiencies.

Conclusions:

The integration of PSO and video image processing advances sports action recognition technology.
The proposed system offers a more intuitive and effective method for sports training analysis.
This technology has the potential to significantly improve athletic performance and training outcomes.