Billiard Ball Movement Prediction Using Inference Engine

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Solution Overview

Problem

Current methods for assessing billiard ball movement in cue sports are subjective and lack precision, making it difficult for players to correlate their strokes with the resulting ball movement metrics.

Innovation Solution

A method and system for predicting billiard ball movement using captured imagery processed by an inference engine trained on annotated video data, providing real-time metrics such as velocity, spin, and trajectory.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If subjective observation methods are used to assess billiard ball movement, then the assessment process is simple and requires no complex equipment, but the measurement precision and accuracy of movement metrics are insufficient

Engineering Contradiction:
Improvemeasurement precisionVSAvoiddevice complexity
Core Design Contradiction:
Measurement precisionVSDevice complexity

Solution Approach 1:

The patent replaces the mechanical/visual observation system with an optical-digital system. Video cameras capture ball movement, and computer algorithms process the visual data to extract precise metrics such as velocity, spin rate, and trajectory, transforming subjective observation into objective digital measurement.

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The patent introduces video cameras and computer processing systems as intermediaries between the billiard ball movement and the observer. These intermediaries capture, transmit, and analyze movement data, providing precise measurements without requiring direct human observation and interpretation.

Inventive Principle:
Principle #24Intermediary (Mediator)

2Measurement precision

If real-time video capture and analysis systems are implemented to measure ball movement metrics, then measurement precision is improved, but the device complexity and cost increase

Engineering Contradiction:
Improvemeasurement precisionVSAvoiddevice complexity
Core Design Contradiction:
Measurement precisionVSDevice complexity

Solution Approach 1:

The system uses multi-functional components that serve multiple purposes. For example, the video camera not only captures ball position but can also track spin, velocity, and trajectory. The computer system performs multiple analysis functions including metric extraction, comparison with target metrics, and performance evaluation, reducing the need for separate specialized devices.

Inventive Principle:
Principle #6Universality (Multi-functionality)

Solution Approach 2:

The system is designed to be self-sufficient in capturing and analyzing all necessary movement metrics. The video capture and processing system automatically extracts velocity, spin, and trajectory data without requiring additional sensors or manual measurement tools, making the system more integrated and potentially more cost-effective.

Inventive Principle:
Principle #25Self-service

3Loss of information

If multiple movement metrics are tracked and analyzed, then the performance feedback completeness is improved, but the data processing complexity increases

Engineering Contradiction:
Improveperformance feedback completenessVSAvoiddata processing complexity
Core Design Contradiction:
Loss of informationVSDevice complexity

Solution Approach 1:

The patent segments the complex task of performance analysis into distinct metric components: velocity, spin rate, trajectory, and other movement parameters. Each metric is extracted and analyzed separately by the computer system, allowing for comprehensive feedback while managing data processing through modular analysis of individual parameters.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The system implements feedback mechanisms where captured movement metrics are compared against target metrics, and performance evaluations are provided to players. This feedback loop helps players understand their performance across multiple dimensions and make adjustments, with the computer system automatically managing the comparison and evaluation processes.

Inventive Principle:
Principle #23Feedback

Data Source

PatentUS20250032893A1Billiard ball movement metrics prediction for performance feedback
Publication Date: 2025.01.30 SEYBERTS BILLIARD CORP
  • US20250032893A1 patent drawing
  • US20250032893A1 patent drawing
  • US20250032893A1 patent drawing

AI summary

Billiard ball movement prediction includes capturing imagery of a billiard ball while in motion and submitting the imagery to an inference engine trained to predict a metric of movement of the billiard ball based upon the captured imagery. Thereafter, the predicted metric of movement is transmitted to a remote computing device for viewing by the end user. In one aspect of the embodiment, the inference engine is trained with annotated video imagery including known speed, revolutions, angular direction and angular momentum. As such, the predicted metric can then include a predicted velocity of the billiard bill, a number of revolutions of the billiard ball during travel along the pool table, an angular direction of movement of the billiard ball relative to a direction of movement of a cue striking the billiard ball, and an angular momentum demonstrated by the movement of the billiard ball.