VR Depth Perception Calibration Using User Grid Alignment
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Solution Overview
Problem
Existing virtual reality (VR) systems fail to accurately render three-dimensional (3D) images due to variations in individual depth perception among users, as optical eye tracking is not precise enough to account for unique factors such as the center of projection, retinal light formation, and blind spots.
Innovation Solution
A system that determines and adjusts for individual depth perception by allowing users to input adjustments on a display, applying offsets to render 3D objects based on their unique perspective, using a transparent display with a grid pattern for alignment and potentially incorporating head-mounted displays (HMDs) or multi-display assemblies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If optical eye tracking is used to determine user depth perception, then the system can automatically capture eye position data, but the depth perception rendering remains inaccurate due to individual variations in eye anatomy and perception
Solution Approach 1:
The system presents a virtual grid pattern and receives user feedback by adjusting the grid alignment through user input devices. The processor analyzes this feedback to determine individual depth perception offsets, creating a closed-loop calibration process that refines the rendering accuracy based on actual user perception rather than relying solely on automated eye tracking estimates.
Solution Approach 2:
The system determines multiple offset parameters (scale offset, rotation offset, position offset) based on user feedback and applies these parameters to transform the virtual grid pattern. These parameter changes allow the system to compensate for individual variations in depth perception by adjusting the rendering parameters according to each user's specific anatomical and perceptual characteristics.
2Productivity
If a standard virtual grid pattern is presented without user customization, then the rendering process is simple and fast, but the depth perception rendering does not account for individual user variations leading to inaccurate 3D object rendering
Solution Approach 1:
The system performs depth perception calibration before the actual 3D object rendering. By presenting the virtual grid pattern and collecting user feedback in advance, the system pre-determines the individual offset parameters. This preliminary calibration action allows the subsequent rendering process to use optimized, pre-calculated parameters, maintaining rendering speed while achieving high accuracy.
Solution Approach 2:
The calibration process requires the user to actively participate by providing feedback on grid alignment. The user's own perception and adjustment actions directly determine the rendering parameters, making the system adapt to individual user characteristics through self-service calibration rather than relying on generic default settings or purely automated estimation.
3Measurement precision
If individual depth perception calibration is performed for each user, then rendering accuracy is improved, but the system complexity and calibration time increase
Solution Approach 1:
The system extracts only the essential calibration information needed for depth perception rendering by presenting a simplified virtual grid pattern. Instead of requiring complex calibration procedures or multiple types of input devices, the system isolates the key calibration task to grid alignment, which can be accomplished through straightforward user feedback mechanisms.
Solution Approach 2:
The virtual grid pattern serves multiple functions: it acts as a calibration target for determining depth perception offsets, provides a visual reference for user alignment feedback, and enables the system to calculate multiple rendering parameters (scale, rotation, position) simultaneously. This multi-functional approach reduces the need for separate calibration tools and procedures.
Data Source
AI summary
Techniques are described for determining a user's unique depth perception in viewing virtual objects in virtual reality (VR) to make the VR experience more accurate and immersive for the user. The user can align a virtual image the user sees with a real-world image behind the virtual image to provide input indicating the user's depth perception. Depth perception parameters can then be determined from that for subsequently rendering VR objects to that user.