Application of Moving Target Information Perception Technology in Intelligent Supervision System

Area of Science:

• Computer Vision and Sports Science
• Intelligent Systems and Biomechanics

Background:

• Traditional sports injury data collection methods suffer from inaccuracies, incompleteness, and image inconsistencies.
• Existing methods lack the ability to capture dynamic motion and potential damage postures effectively.

Purpose of the Study:

• To propose an application of moving target information perception technology for intelligent sports injury supervision.
• To develop a system that overcomes the limitations of traditional data collection in sports injury analysis.
• To enable accurate and timely detection of potential motion-related damage in athletes.

Main Methods:

• Utilized intelligent tracking image analysis to judge potential motion damage postures.
• Developed an intelligent video surveillance target tracking simulation system using target detection and tracking algorithms.
• Integrated OpenCV computer vision and QT image libraries for system development.

Main Results:

• The developed system accurately collects sports injury attitude information without continuous value calculations.
• The intelligent tracking image matrix addresses shortcomings of traditional disconnected images, improving data completeness.
• Three-dimensional image analysis allows for multi-angle assessment of damage attitudes.

Conclusions:

• The proposed method significantly improves the accuracy and completeness of sports injury data collection.
• The intelligent video surveillance system effectively realizes target tracking for injury prevention.
• This approach offers a robust solution for analyzing and preventing motion-related injuries in sports.