3D Display Gaze Tracking for Viewer-Specific Projection Rendering
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Solution Overview
Problem
Existing 3D displays often project images to multiple viewers without considering their individual positions and gaze directions, leading to distorted or broken images due to inadequate viewing angles or distances, wasting processing resources and causing poor user experiences.
Innovation Solution
Implement deep learning systems for face detection, gaze tracking, and camera image evaluation to determine viewer-specific 3D projections by analyzing face and eye landmarks, head pose, and eye tracking information, ensuring accurate rendering based on each viewer's point of regard and position relative to the display.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If 3D displays project images to multiple viewers without considering individual positions and gaze directions, then the display can serve multiple users simultaneously, but the images become distorted or broken due to inadequate viewing angles or distances
Solution Approach 1:
The system calculates viewer-specific 3D projections by determining individual gaze directions and positions, then renders images with different properties for each viewer. The rendering parameters (projection angles, depth positioning, distortion correction) are locally optimized for each viewer's specific viewing conditions rather than using a single uniform projection for all viewers.
Solution Approach 2:
The system dynamically adjusts projection parameters in real-time based on tracked viewer positions and gaze directions. As viewers move or change their viewing angles, the system continuously updates the 3D projection parameters to maintain optimal image quality, transforming static projections into adaptive, dynamic rendering that responds to viewer behavior.
2Measurement precision
If the system processes all camera image feeds for gaze tracking, then complete viewer information is obtained, but processing resources are wasted on useless or low-quality image data
Solution Approach 1:
The system extracts and processes only the essential information needed for gaze tracking from camera feeds. It identifies and processes only those image feeds that contain useful gaze data, filtering out redundant or low-quality feeds. This selective processing approach maintains accurate gaze tracking while significantly reducing computational overhead by ignoring unnecessary image data.
Solution Approach 2:
The system applies partial processing to camera feeds, processing only the portion of image data that contains relevant gaze information. It evaluates image quality metrics and processes only up to the point where useful gaze data is extracted, avoiding unnecessary processing of the entire image feed when quality thresholds are not met.
3Adaptability or versatility
If the system renders 3D projections for all viewers simultaneously, then all users receive personalized content, but processing time increases and latency occurs
Solution Approach 1:
The system performs preliminary calculations of projection parameters and pre-processes rendering tasks before actual display. It anticipates viewer positions and gaze directions, pre-calculates projection transformations, and prepares rendering data in advance. This allows the system to reduce real-time processing delays and minimize rendering latency while maintaining personalized content delivery.
Data Source
AI summary
Methods, systems, and storage media for projecting multi-viewer-specific 3D object perspectives from a single 3D display are disclosed. Implementations may: acquire face and eye region image data of a plurality of viewers within a field of view of at least one camera associated with a 3D-enabled digital display; analyze the eye region image data to determine at least one 3D eye position, at least one eye state, at least one gaze angle, and at least one point-of-regard for at least one viewer relative to at least one camera associated with the 3D-enabled digital display; and calculate a plurality of image projections for display by the single 3D display.