Mobile Camera Bat Tracking for Real-Time Swing Analysis
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Solution Overview
Problem
Conventional methods for analyzing baseball swing mechanics are hindered by the need for intrusive sensors, high costs, and limited flexibility, making it difficult for players to receive immediate and accurate feedback in various batting practice settings.
Innovation Solution
A mobile camera-based system using computer vision and machine learning to detect bat keypoints in video frames, predicting swing metrics like bat speed and attack angle in real-time, without the need for external sensors, and providing instant feedback through a user-friendly app.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensor-based approaches like Blast Motion and Diamond Kinetics are used, then measurement precision is improved, but device complexity and cost increase due to requiring physical sensors attached to the bat knob and Bluetooth connectivity infrastructure
Solution Approach 1:
The patent replaces the mechanical sensor attachment system with a computer vision-based optical measurement system. Instead of physically attaching sensors to the bat knob and using Bluetooth connectivity, the system uses mobile cameras to capture swing motion and processes the video data through computer vision algorithms to extract swing metrics, thereby eliminating the complex mechanical sensor infrastructure while maintaining measurement capability
Solution Approach 2:
The patent creates a visual copy representation of the bat and swing motion through video frames. Instead of directly measuring the physical bat with sensors, the system captures the bat's appearance and motion in video frames, then uses image processing algorithms to extract positional information and infer swing parameters from the visual copy, avoiding the need for physical sensor attachment
2Measurement precision
If marker-based motion capture is used, then measurement precision is improved, but ease of operation deteriorates due to requiring expensive specialized lab environments, extensive setup, and laborious data cleaning
Solution Approach 1:
The patent extracts the essential measurement function from the complex marker-based motion capture system. Instead of requiring specialized labs, markers, and extensive setup, the system extracts swing analysis capability from the video stream itself, using computer vision algorithms to directly detect bat position and motion from standard mobile camera footage, thereby simplifying the operational requirements while maintaining precision
Solution Approach 2:
The patent makes the analysis system universal by working with standard mobile cameras rather than requiring specialized motion capture equipment. The same mobile camera used for general purposes is leveraged for swing analysis, eliminating the need for expensive specialized lab environments and extensive setup procedures while maintaining measurement quality
3Adaptability or versatility
If multi-camera stadium installations are used, then adaptability is improved for multi-person use, but cost increases significantly and flexibility is limited to specific batting boxes and company cameras
Solution Approach 1:
The patent enables self-service analysis where individual players can use their own mobile cameras to capture and analyze their own swings without requiring stadium installations or company-provided equipment. The system is designed to work with any mobile device camera, allowing players to independently perform swing analysis in their own batting practice settings, thereby reducing dependency on expensive infrastructure
Solution Approach 2:
The patent replaces expensive, permanent stadium camera installations with inexpensive, portable mobile cameras. Instead of investing in costly multi-camera stadium systems, the system leverages the already-owned mobile devices that players carry, providing affordable access to swing analysis without requiring permanent infrastructure installation
4Measurement precision
If conventional sensor-based systems are used, then measurement precision is improved, but ease of operation deteriorates as sensors can disrupt a player's natural feel and require Bluetooth connectivity
Solution Approach 1:
The patent substitutes the physical sensor attachment system with a non-contact optical measurement system. Instead of attaching sensors to the bat that can disrupt the player's natural feel, the system uses mobile cameras to capture swing motion from a distance and processes the visual data to extract swing mechanics, thereby maintaining player comfort and natural movement patterns while preserving measurement precision
Data Source
AI summary
A mobile camera-based system and method provides real-time analysis and feedback on baseball swing performance using computer vision and machine learning techniques. The system comprises a mobile application that captures high-frame-rate video of a hitter's swing using one or two smartphone cameras. A custom YOLO-based pose estimation model detects and localizes key points on the bat in each video frame. The extracted bat trajectories are then processed and input into an XGBoost machine learning model to predict critical swing metrics like bat speed, attack angle, and time to contact. The predicted metrics are displayed to the user through intuitive visualizations in the app's interface within seconds of the swing, enabling instant feedback and adjustment. Swing data is stored locally on the device and can be uploaded to a central server for further analysis, aggregation, and reporting.