Gaze-Based Image Processing for VR Bandwidth Reduction
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Solution Overview
Problem
The increasing demand for higher resolution and refresh rates in display devices leads to a significant increase in image data transmission requirements, posing challenges for bandwidth and transmission pressure in virtual reality systems and other display applications.
Innovation Solution
An image processing method and system that determines a display mode based on the application type, user operation, or number of viewers, processing original image data to reduce resolution in non-gaze areas and segmenting images accordingly, allowing for efficient data transmission while maintaining optimal display quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the resolution and refresh rate of display devices are increased, then the image quality and display performance are improved, but the transmission bandwidth requirement increases significantly
Solution Approach 1:
The display area is segmented into multiple regions based on user gaze behavior. The region of interest (ROI) where the user is looking receives full resolution processing, while peripheral regions use lower resolution. This segmentation allows the system to maintain high image quality in critical areas while reducing overall data transmission requirements.
Solution Approach 2:
Different resolution qualities are applied to different spatial locations within the same image frame. The ROI experiences high-resolution rendering to ensure visual clarity, while non-ROI areas use compressed lower-resolution data. This local quality differentiation optimizes the balance between perceived image quality and transmission bandwidth consumption.
2Quantity of substance
If the resolution of target image data is reduced, then the transmission bandwidth is reduced, but the image display quality may deteriorate
Solution Approach 1:
The system performs preliminary processing to identify the region of interest (ROI) based on user gaze parameters before generating the final image data. By pre-determining which areas require high resolution, the system can allocate computational resources efficiently and ensure that quality reduction in non-ROI areas does not impact overall perceived quality.
Solution Approach 2:
The image processing system adaptively adjusts resolution allocation based on real-time gaze detection feedback. The system serves itself by using gaze data to automatically determine which regions merit high-resolution processing, eliminating the need for manual quality settings and optimizing the bandwidth-quality tradeoff dynamically.
3Adaptability or versatility
If multiple display modes are supported, then the adaptability to different usage scenarios is improved, but the device complexity increases
Solution Approach 1:
The image processing system is designed with multi-functionality to handle various display modes including 2D, 3D, and light field displays through a unified processing framework. The same gaze-based ROI identification and differential resolution processing methodology applies across all display modes, reducing the need for mode-specific processing logic and managing system complexity.
Data Source
AI summary
An image processing method includes determining a display mode; processing, according to an image processing manner corresponding to the display mode, original image data to obtain target image data; and transmitting the target image data to an image display terminal, so that the image display terminal performs image display according to a scanning display manner corresponding to the display mode, a resolution of the target image data is less than or equal to that of the original image data, and the target image data carries indication information of the display mode.