AR LED State Detection via Homography Matrix
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Solution Overview
Problem
Current augmented reality systems face challenges in accurately detecting LED states without confusing multiple LEDs on a single panel, while being non-computationally expensive and user-friendly for non-expert users.
Innovation Solution
A system utilizing a mobile device camera to capture video of LEDs, processing it with a computer to determine feature points, matching these with reference images to compute a homography matrix, and transforming the image to determine LED states by comparing zone values with reference values, displayed on the mobile device.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If computer vision with deep learning is used to detect object states, then detection capability is improved, but computational expense increases
Solution Approach 1:
The patent segments the LED detection problem into distinct processing stages: capturing video frames, detecting individual LED positions, determining their states (on/off), and decoding the combined information. This segmentation allows each stage to be optimized independently, reducing overall computational expense while maintaining detection accuracy.
Solution Approach 2:
The patent employs preliminary action by using template matching to pre-identify LED positions and characteristics before full state detection. Reference images with known LED patterns are used to establish expected positions and appearances, allowing the system to quickly locate and interpret LED states without performing exhaustive analysis on every frame.
2Loss of information
If multiple LEDs on a single panel are detected, then information coverage is improved, but detection accuracy decreases due to confusion
Solution Approach 1:
The patent applies segmentation by detecting and analyzing each LED individually within the panel. The system identifies separate LED positions and determines their states independently, then combines this information to decode the overall device state. This prevents confusion between adjacent LEDs while maintaining complete information coverage.
Solution Approach 2:
The patent introduces an intermediary decoding layer that translates individual LED states into meaningful device status information. Rather than directly interpreting raw LED patterns, the system uses a decoding mechanism that maps specific LED configurations to device states, reducing ambiguity and improving detection accuracy.
3Speed
If real-time LED detection is implemented, then responsiveness is improved, but computational complexity increases
Solution Approach 1:
The patent implements periodic action by analyzing LED states at regular intervals through continuous video capture and frame processing. Rather than attempting continuous real-time analysis of every pixel change, the system processes frames at a steady rate, balancing responsiveness with computational manageability.
Solution Approach 2:
The patent extracts only the essential information needed for LED state detection from video frames, rather than processing complete image data. By focusing computational resources on detecting specific LED positions and states rather than analyzing entire frames, the system achieves real-time performance with reduced complexity.
Data Source
AI summary
A system to detect LEDs and their states in an AR context is provided having a monitored device having a plurality of LEDs; a computer receives a picture of the monitored device and LEDs; the computer processes said picture to determine a plurality of feature points; a database is in data communication with said computer that stores a plurality of reference images with reference feature points and reference zones; the computer matches at least some of the plurality of feature points with at least some of the plurality of reference feature points to compute a homography matrix; the computer transforms the picture into a transformed picture using the homography matrix; the computer processes zones of the transformed picture based on the reference zones to determine the state of each of the plurality of LEDs by comparing a value of the picture in the zone with a reference value.