Golf Swing Analysis Using Personalized Motion Models
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Solution Overview
Problem
Current golf training methods using auxiliary devices and image recognition face challenges such as discomfort due to sensor wear, discrepancies with actual golf scenarios, and the difficulty in adapting to individual physical qualities and skills, leading to reduced learning enthusiasm and potential injuries.
Innovation Solution
A method that captures user swing videos and simulator data to analyze and compare swing actions with an optimal personal swing model, providing feedback and suggestions for improvement, using human body key points, action features, and data analysis to align and compare swing actions and results, allowing for personalized training.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If auxiliary devices with detection sensors are worn during golf training, then action detection precision is improved, but ease of operation deteriorates due to uncomfortable limb movements
Solution Approach 1:
The patent replaces mechanical sensor-based detection systems with an optical vision system using multiple cameras to capture and analyze golf swing actions. This eliminates the need for wearable sensors that restrict movement, while maintaining high measurement precision through image processing and human body key point analysis.
2Manufacturing precision
If a constant standard reference model is used for action comparison, then manufacturing precision is improved, but adaptability deteriorates because it does not account for individual physical qualities
Solution Approach 1:
The patent transitions from a static, constant reference model to a dynamic personal model that is established through initial coaching and can be updated over time. This personal model adapts to the trainee's individual physical qualities and skill level, allowing for customized action standards that evolve with the trainee's progress.
Solution Approach 2:
The system changes the parameters of the reference model from fixed universal standards to variable personal parameters specific to each trainee. By adjusting the reference model based on individual characteristics and progress, the system maintains precision while improving adaptability to different physical qualities.
3Manufacturing precision
If forced imitation of famous golf stars' actions is required, then manufacturing precision is improved through standardized actions, but object-generated harmful factors increase due to potential sports injuries
Solution Approach 1:
The patent applies local quality by customizing the reference model to match each trainee's specific physical conditions and capabilities. Instead of forcing uniform imitation of professional golfers, the system creates localized, personalized action standards that are safe and appropriate for each individual's body type and skill level.
4Reliability
If full-time coaches are used for golf training, then reliability of training guidance is improved, but loss of energy increases due to high training costs
Solution Approach 1:
The patent enables self-service training by providing an automated system that captures video, analyzes swing actions, compares them against personal models, and generates feedback without requiring constant coach intervention. The system maintains reliable guidance through automated analysis while significantly reducing the need for expensive full-time coaching.
Solution Approach 2:
The system implements automated feedback loops where swing actions are captured, analyzed, compared with personal models, and evaluated with suggestions for improvement. This automated feedback mechanism provides reliable training guidance that reduces dependency on expensive human coaches while maintaining high-quality instruction.
Data Source
AI summary
The invention provides a method for assisting golf training and a computer program product. The method includes: capturing a video of current swing by a user and simulator data; analyzing a swing action by using human body key points, to obtain swing stages and corresponding key point set sequences; determining a plurality of action features corresponding to the current swing; comparing the plurality of action features of the current swing with a plurality of action features corresponding to an optimal personal swing model to obtain an action difference between the current swing and the optimal personal swing model; and according to the simulator data, determining a result difference between the current swing and the optimal personal swing model. With the utilization of the above technical solution, golf playing skills can be improved according to physical conditions of the user.