Predictive AR Rendering to Reduce Latency
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Solution Overview
Problem
Virtual and augmented reality systems face latency issues due to limitations in processing speed, causing augmented reality content to lag behind user orientation changes, leading to a deterioration in user experience.
Innovation Solution
The system predictively renders images by generating multiple images based on anticipated user orientations, allowing the AR device to select the most appropriate image from a pre-rendered set rather than continuously rendering in real-time, reducing processing power requirements and latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If real-time rendering is performed to respond to user orientation changes, then responsiveness is improved, but processing power requirements and latency increase
Solution Approach 1:
The system pre-renders multiple images for different anticipated user orientations before the actual rendering is needed. This preliminary action allows the AR device to select from pre-computed images rather than performing real-time rendering, reducing processing power requirements while maintaining responsiveness.
Solution Approach 2:
The system dynamically adapts the number and types of pre-rendered images based on user behavior patterns and orientation change predictions. This allows the system to optimize processing resources by rendering only the necessary number of predictive images, balancing responsiveness with processing power consumption.
2Manufacturing precision
If continuous real-time rendering is performed to maintain accurate overlay, then accuracy is improved, but latency increases
Solution Approach 1:
The system performs preliminary rendering of multiple predictive images for different future orientations before the actual display moment. This eliminates the latency associated with real-time rendering while maintaining accuracy by selecting the pre-rendered image that best matches the actual user orientation at display time.
Solution Approach 2:
The system creates multiple copies of the augmented reality scene rendered at different anticipated orientations. Instead of rendering a single real-time image, the system prepares multiple predictive copies in advance, then selects the appropriate copy based on actual user orientation, reducing latency while preserving accuracy.
3Manufacturing precision
If high processing power is allocated to AR device for real-time rendering, then rendering quality is improved, but device complexity and cost increase
Solution Approach 1:
The system extracts the computationally intensive rendering task from the AR device and performs it in advance during periods of low user interaction or using less powerful processing units. This allows high rendering quality without requiring the AR device itself to have continuously high processing power or complex hardware.
Solution Approach 2:
The system performs complex rendering calculations beforehand during low-demand periods or using cloud computing resources, then delivers simplified image data to the AR device for display. This preliminary action reduces the processing burden on the AR device during actual use, lowering device complexity requirements.
Data Source
AI summary
Embodiments herein include an augmented reality (AR) system that predictively renders images which may reduce or remove lag. Instead of rendering images in response to sensing changes in the user orientation, the AR system generates predictive images by predicting future user orientations. The AR system can render multiple predictive images that each includes AR content that will be displayed at a future time. Because the predictive images are generated using different user orientations, the location of an object in the AR content in each of the predictive images is different. The predictive images are transmitted to the AR device which selects one of the images to display by comparing the orientations used to generate each of the predictive images with the current (actual) orientation of the user.