Eye Tracking Visual Range Mapping Calibration
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Solution Overview
Problem
Eye tracking devices struggle to accurately map the visual range of viewers to the screen range due to variations in viewing location and personal habits, leading to deviations that require calibration for precise visual popularity analysis.
Innovation Solution
A visual range mapping method and system that receives eye detection results, generates a visual range, compares it with the display range to calculate a calibration value, and maps the visual range to the display range, ensuring precision in visual popularity analysis by using a processing device coupled with an eye detection device and a screen.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If eye tracking device detects visual range without calibration, then measurement process is simple and fast, but measurement precision deteriorates due to deviation between visual range and screen range
Solution Approach 1:
The patent performs calibration before actual eye tracking measurement by displaying calibration images at multiple positions and recording corresponding eye detection results. This preliminary calibration establishes mapping relationships between visual range coordinates and screen coordinates, ensuring high measurement precision in subsequent actual use without requiring calibration during each measurement session.
2Measurement precision
If calibration procedure is performed before eye tracking, then measurement precision is improved, but loss of time increases due to additional calibration steps
Solution Approach 1:
The patent uses calibration images that replicate the visual characteristics and positioning of actual content on the screen. By creating a copy of the screen display environment through calibration images, the system establishes accurate coordinate mappings without requiring time-consuming complex calibration procedures, thus reducing calibration time while maintaining precision.
3Measurement precision
If visual range is mapped to screen range using calibration values, then visual popularity analysis precision is improved, but device complexity increases due to mapping calculations
Solution Approach 1:
The patent transforms coordinate systems by establishing linear mapping relationships between visual range coordinates and screen coordinates through calibration. By changing the parameter representation from uncalibrated eye detection coordinates to calibrated screen coordinates, the system enables precise visual popularity analysis while keeping the mapping process computationally efficient through straightforward coordinate transformation formulas.
Data Source
AI summary
A method of visual range mapping includes receiving a plurality of eye detection results from at least one eye tracking device and a display range from a display device, generating a visual range according to the plurality of eye detection results; comparing the visual range with the display range to generate a calibration value, and mapping the visual range into the display range according to the calibration value.