Casino Table Image Normalization for Accurate Gaming Object Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing casino table game monitoring systems are prone to errors and labor-intensive due to sensitivity to camera angle, mounting position, and table orientation, leading to inaccuracies in image analysis.
Innovation Solution
A system that uses geometric transformations and calibration markers to normalize oblique camera images into a perpendicular, overhead view, applying a stored template representation of the gaming table layout to accurately detect and interpret gaming objects, utilizing existing surveillance infrastructure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual monitoring is used, then labor intensity is high and errors are frequent, but system complexity is low
Solution Approach 1:
The patent replaces manual mechanical monitoring with an automated computer vision system that uses cameras, processors, and software algorithms to detect and track gaming objects, eliminating human labor while improving accuracy and consistency
Solution Approach 2:
The system creates digital copies of the gaming table scene through multiple camera views and generates virtual representations (normals) that can be processed and analyzed without physically manipulating the actual gaming environment
2Measurement precision
If camera angle and mounting position are optimized for each table, then monitoring precision improves, but device complexity and installation difficulty increase
Solution Approach 1:
The system dynamically adjusts image processing parameters including geometric transformations, perspective corrections, and normalization factors based on the specific camera angle and mounting position, allowing any camera placement to achieve accurate monitoring through computational compensation rather than physical optimization
Solution Approach 2:
The patent introduces an intermediary processing layer that includes calibration markers and normalization algorithms, which mediate between the raw camera images and the final analysis, correcting distortions and standardizing perspectives without requiring direct optimization of the camera hardware
3Measurement precision
If geometric transformation is applied to correct perspective distortion, then measurement precision improves, but processing time and computational complexity increase
Solution Approach 1:
The system performs preliminary calibration by detecting calibration markers and computing transformation matrices in advance, so that when actual gaming objects need to be measured, the complex geometric transformations can be applied more quickly using pre-computed parameters
Solution Approach 2:
The image processing is segmented into distinct stages: calibration marker detection, geometric transformation computation, normalization application, and object detection, allowing each stage to be optimized independently and enabling parallel processing where applicable
Data Source
AI summary
A system and method for improving monitoring of a casino gaming table that includes capturing a camera image or video feed of a gaming table layout; identifying a calibration marker having a known geometric configuration positioned on the gaming table layout; generating a normalized, substantially top-down digital representation of the gaming table layout; applying a stored template representation of the gaming table layout onto the normalized, substantially top-down representation of the gaming table layout such that each of the pre-determined regions of interest is spatially aligned with corresponding locations in the normalized, substantially top-down representation of the gaming table layout; detecting presence of a gaming object within at least one of the predetermined regions of interest; correlating the detected gaming object with a stored template representation of the gaming object; and generating, gameplay data derived from the detected physical gaming object.