IR Emitter Saturation Correction for HMD Depth Accuracy
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Solution Overview
Problem
Head-mounted displays for augmented and virtual reality systems face challenges in accurately measuring depth due to over or under saturation of infrared light patterns, especially in collaborative sessions where multiple headsets emit light towards the same objects, leading to inaccurate depth measurements and potential oversaturation or undersaturation of images.
Innovation Solution
An IR emitter saturation correction system that iteratively adjusts the intensity of infrared emitters based on histogram brightness values to identify and correct over or under saturation, using a binary divide-and-conquer approach to ensure accurate image capture and maintain minimum accuracy tolerances for depth measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple headsets emit infrared light simultaneously in collaborative sessions, then the coverage area and collaborative functionality are improved, but image saturation occurs leading to decreased measurement precision
Solution Approach 1:
The system dynamically adjusts the intensity of infrared emitters based on real-time detection of image saturation levels. When multiple headsets are detected in collaborative sessions, the system automatically modifies emitter brightness to prevent oversaturation, enabling continuous accurate depth measurement throughout the user session.
Solution Approach 2:
The system implements a feedback mechanism where captured images are analyzed for saturation levels, and this information is used to adjust infrared emitter intensity. The histogram analysis of captured images provides feedback that triggers intensity adjustments, creating a closed-loop control system that maintains measurement precision during collaborative use.
2Measurement precision
If infrared emitter intensity is increased to improve depth measurement accuracy, then measurement precision is improved, but over saturation of images occurs
Solution Approach 1:
The system changes the intensity parameter of infrared emitters based on detected saturation conditions. By monitoring image histograms and identifying saturation levels, the system adjusts emitter intensity to optimal values that prevent oversaturation while maintaining sufficient signal strength for accurate depth measurement.
Solution Approach 2:
The system applies partial action by adjusting only the intensity parameter of infrared emitters rather than other parameters. This targeted adjustment of a single parameter (intensity) allows precise control over image saturation while maintaining measurement accuracy, avoiding the need to modify multiple system parameters simultaneously.
3Illumination intensity
If infrared emitter intensity is decreased to prevent over saturation, then image saturation is reduced, but under saturation occurs leading to decreased measurement precision
Solution Approach 1:
The system dynamically adapts emitter intensity based on real-time conditions rather than using a fixed intensity setting. By continuously monitoring image saturation and adjusting intensity accordingly, the system prevents both oversaturation and undersaturation, maintaining optimal measurement precision throughout varying lighting conditions and collaborative session scenarios.
Solution Approach 2:
The system performs self-adjustment of infrared emitter intensity without external intervention. The automatic detection of saturation conditions and subsequent intensity modifications are handled by the system itself, eliminating the need for manual calibration or external control during collaborative sessions and ensuring continuous measurement accuracy.
4Device complexity
If fixed intensity is used for infrared emitters during calibration, then device complexity is reduced, but adaptability to changing lighting conditions deteriorates
Solution Approach 1:
The system implements feedback control where captured image data is analyzed and used to adjust emitter intensity. This feedback mechanism enables the system to adapt to changing lighting conditions automatically, compensating for variations in ambient light and collaborative session dynamics without requiring complex manual calibration procedures.
Solution Approach 2:
The system performs self-calibration and self-adjustment during operation, eliminating the need for complex external calibration equipment or procedures. By automatically detecting saturation conditions and adjusting emitter intensity, the system maintains adaptability while keeping the control system relatively simple and easy to operate.
Data Source
AI summary
An information handling system operating a wearable headset IR emitter saturation correction system may comprise an infrared emitter emitting IR light, a camera capturing a calibration image and a first session image of the IR light reflected from a landmark, and a SLAM engine generating a first session SLAM frame. A processor may execute code instructions to compare the measured calibration pixel brightness value for each pixel associated with the landmark in a calibration image with a measured first session pixel brightness value for each pixel associated with the landmark in the first session image to determine whether the first session SLAM frame is over or under saturated, and determine an adjusted brightness if the first session SLAM frame is over or under saturated. The infrared emitter may emit light according to the adjusted brightness.