A track and field technical evaluation model based on DeepSORT algorithm and YOLOv5 algorithm

Key Points

• To develop a technical evaluation model for track and field using advanced algorithms.
• Utilized DeepSORT for object tracking in sports scenarios.
• Employed YOLOv5 for real-time object detection during athletic events.
• Analyzed performance metrics based on algorithm outputs.
• Improved accuracy of tracking athletes during competitions.
• Enhanced detection of performance metrics in real-time.
• Demonstrated feasibility of algorithm integration in sports evaluations.