Computer Vision for Pre-Emptive Gaming Table Outcome Management
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Solution Overview
Problem
Existing tracking systems in casino gaming environments struggle to accurately track moving objects such as gaming tokens, interactions with cards or dice, and project gaming content to specific locations on the gaming table, affecting the clarity and accuracy of game outcome information.
Innovation Solution
A gaming system uses image analysis and machine-learning models to determine the outcome value of randomizing game objects, predict winning outcomes, and project virtual-scene overlays at precise locations on the gaming table, conforming to the shape and location of the objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional tracking systems are used to monitor gaming objects, then basic tracking functionality is provided, but tracking accuracy and ability to follow moving objects deteriorates
Solution Approach 1:
The patent replaces traditional mechanical/optical tracking systems with a computer vision-based image analysis system. The system uses image capture devices and processing algorithms to detect, track, and analyze gaming objects, player gestures, and table state, achieving superior tracking accuracy and reliability for moving objects compared to conventional tracking methods.
2Loss of information
If projection systems attempt to display gaming content on table surfaces, then visual information is provided, but clarity and accuracy of outcome information deteriorates due to improper alignment
Solution Approach 1:
The system employs a feedback mechanism where the image analysis system continuously monitors the actual positions of gaming objects and table features, and this information is used to dynamically adjust and recalibrate the projection system. This ensures that projected gaming content and outcome information remain precisely aligned with the physical table surface and relevant game elements, maintaining high clarity and accuracy.
Solution Approach 2:
The system performs preliminary calibration and alignment of the projection system with the gaming table surface before gameplay begins. The image analysis system pre-maps the table geometry, object positions, and projection parameters to ensure accurate content placement from the start of the game, preventing misalignment issues.
3Productivity
If manual monitoring of gaming table events is performed, then basic game management is achieved, but response time and accuracy in detecting game outcomes deteriorates
Solution Approach 1:
The system implements self-service automation where the image analysis system autonomously detects, tracks, and determines game outcomes without requiring manual intervention. The system automatically identifies card values, determines winning/losing conditions, tracks gaming tokens, and monitors player actions, achieving both high response time and accurate outcome detection through automated computer vision processing.
Data Source
AI summary
A system and method for pre-emptively managing game outcomes at a gaming table are disclosed. Using first image data, an outcome value of a randomizing game object is determined before the object reaches its final position. Using second image data of the table surface, a target player station for the object is predicted. Based on the outcome value, predicted station, and game rules, an anticipated winning outcome is detected. In response to detecting the anticipated win, an electronic game management action is initiated. This electronic game management action occurs prior to the game object being revealed at its target station, enabling proactive game security and operational management.