HMD Imaging Sensor Adaptive Exposure for Low-Light Motion Blur
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Solution Overview
Problem
Existing virtual and augmented reality devices face challenges in capturing and displaying images in low-light environments without introducing significant noise or blurring, which can disrupt the user's experience.
Innovation Solution
The system automatically adjusts the frame rate and binning mode of the imaging device in a head-mounted display based on the amount of motion and ambient light conditions, using an inertial measurement unit to determine motion and an optical sensor to assess light levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the frame rate is reduced to increase integration time in low-light conditions, then the signal-to-noise ratio is improved, but motion blur increases
Solution Approach 1:
The system dynamically adjusts the frame rate based on real-time motion detection. When motion is detected, the frame rate is maintained at a higher value to reduce motion blur; when motion is minimal, the frame rate is reduced to increase integration time and improve signal-to-noise ratio. This dynamic adaptation resolves the contradiction by making the frame rate flexible rather than fixed.
Solution Approach 2:
The system changes the frame rate parameter based on motion conditions. By monitoring motion and adjusting the frame rate parameter accordingly, the system optimizes the balance between signal-to-noise ratio and motion blur, transforming a static parameter into a conditional variable that adapts to environmental factors.
2Measurement precision
If pixel binning is applied to reduce noise in low-light conditions, then the signal-to-noise ratio is improved, but the spatial resolution is reduced
Solution Approach 1:
The system applies pixel binning selectively based on motion detection. When motion is detected, pixel binning is reduced or disabled to maintain spatial resolution; when motion is minimal, pixel binning is increased to improve signal-to-noise ratio. This local adaptation allows different regions of the image sensor to operate at different binning levels, optimizing both noise reduction and resolution preservation.
Solution Approach 2:
The pixel binning level is dynamically adjusted based on motion conditions rather than being fixed. The system transitions between different binning modes (e.g., 1x1, 2x2, 4x4) depending on the detected motion, allowing the spatial resolution to adapt to the current scene requirements while maintaining optimal signal-to-noise ratio.
3Measurement precision
If the exposure time is increased to capture more light in low-light conditions, then the signal-to-noise ratio is improved, but motion blur increases
Solution Approach 1:
The exposure time parameter is dynamically changed based on motion detection. When motion is detected, the exposure time is reduced to minimize motion blur; when motion is minimal, the exposure time is increased to maximize light capture and improve signal-to-noise ratio. This parameter adaptation resolves the contradiction by making exposure time conditional on scene dynamics.
Solution Approach 2:
The system uses motion detection feedback to continuously adjust exposure time. The motion detector provides real-time feedback about scene dynamics, which the system uses to modify the exposure time parameter, creating a closed-loop control system that optimizes the balance between light capture and motion blur prevention.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances the signal-to-noise ratio of captured images by increasing integration time and applying pixel binning, thereby improving image quality in low-light conditions while minimizing motion blur and latency.
Implementation Method 1
determining an amount of motion of the head-mounted display system based on one or more signals received from an inertial measurement unit included in the head-mounted display system
Implementation Method 2
an optical sensor to assess light levels
Implementation Method 3
enhances the signal-to-noise ratio of captured images by increasing integration time
Implementation Method 4
applying pixel binning, thereby improving image quality in low-light conditions
Data Source
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AI summary
One aspect of this disclosure includes a method for operating a head-mounted display system that includes an imaging device. The method includes receiving an indication that an ambient light condition in an environment is below a lighting threshold. Responsive to the low lighting condition, an amount of motion of the head-mounted display relative to the environment is determined based on one or more signals received from an inertial measurement unit included in the head-mounted display system. An exposure time, frame rate, and a pixel-binning mode are automatically selected for the imaging device based on the determined amount of motion. Imagery is captured from the environment using the automatically selected exposure time, frame rate, and pixel-binning mode for the imaging device. The captured imagery is then displayed at the head-mounted display system.