CNN-Based Digital Playbook Digitization
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Solution Overview
Problem
Current methods for illustrating and sharing sports plays lack standardization, leading to inefficiencies in digitization and dissemination among team members, resulting in prolonged training times and increased risk of human error, which can impact team performance and profitability.
Innovation Solution
Implementing a convolutional neural network (CNN) to automatically identify and classify play features from images, enabling rapid digitization and standardization of playbooks, and converting them into digital formats for easier sharing and analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual digitization methods are used to convert playbooks to digital format, then customization and flexibility in play illustration are maintained, but the time required for digitization increases and human error risk increases
Solution Approach 1:
The system enables self-service automated digitization where the computer system automatically detects play illustrations, extracts features, and converts them to digital format without requiring manual intervention, thereby reducing both time and human error while maintaining accuracy
Solution Approach 2:
The patent replaces manual mechanical digitization processes with an automated computer-based system using image processing and machine learning algorithms to detect and convert play illustrations, eliminating human error and significantly reducing digitization time
2Reliability
If standardized detection methods are implemented for play features, then consistency and reliability improve, but the system becomes less adaptable to different illustration styles and sports
Solution Approach 1:
The system implements universal feature detection capabilities that can identify and process play illustrations across multiple sports and illustration styles through a single automated system, maintaining both consistency and adaptability simultaneously
Solution Approach 2:
The system dynamically adjusts detection parameters and thresholds based on the specific sport and illustration style being processed, allowing standardized detection methods to adapt to different contexts while maintaining reliability
3Productivity
If automated computer systems are used to detect and convert play features, then productivity and speed increase, but the complexity of the system increases
Solution Approach 1:
The system segments the complex digitization process into distinct automated modules including image processing, feature detection, and digital conversion, making the overall system more manageable while maintaining high productivity
Solution Approach 2:
The system introduces an intermediary automated processing layer between manual play illustration and digital format, using machine learning models to bridge the gap and enable high-speed conversion without requiring direct human involvement in the complex detection process
Data Source
AI summary
Methods and systems for automatically creating a digital playbook. A processor receives image data. The processor stores the image data in memory. The processor detects a first play illustration in the image data. The processor analyzes the first play illustration. Based on the analysis of the first play illustration, the processor detects features of the play. The processor generates a data file for the first play. The processor stores the data file for the first play in memory.