Rendered-Image Reprojection for Low-Latency Camera Pose Matching
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Solution Overview
Problem
Rendering virtual content in real time for extended reality applications requires significant computational resources and can be prone to latency due to the need to match the perspective of multiple user devices or a moving camera, especially when creating convincing virtual environments.
Innovation Solution
A computing device generates images based on already rendered content by considering the difference in camera pose, using techniques such as deprojection and reprojection, and inpainting to reduce computational load and latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If real-time rendering is performed for multiple camera poses to match user device perspectives, then perspective accuracy is improved, but computational resources and latency increase
Solution Approach 1:
The system pre-renders images for a discrete set of camera poses before they are actually needed. By anticipating future camera positions and pre-computing the corresponding rendered images, the system eliminates the need for speculative rendering when the actual pose is determined, thereby reducing latency and computational overhead while maintaining perspective accuracy.
Solution Approach 2:
The system dynamically adapts the rendering process by continuously monitoring actual camera poses and comparing them against pre-rendered poses. When a match is found or a close approximation is identified, the system selectively applies or blends pre-rendered images rather than performing full real-time rendering, thus optimizing computational resource usage while preserving perspective fidelity.
2Adaptability or versatility
If speculative rendering is performed for multiple potential camera poses, then perspective matching capability is improved, but latency increases
Solution Approach 1:
The system pre-renders images for a discrete set of camera poses before they are actually needed. By anticipating future camera positions and pre-computing the corresponding rendered images, the system eliminates the need for speculative rendering when the actual pose is determined, thereby reducing latency and computational overhead while maintaining perspective accuracy.
3Measurement precision
If images are rendered for each specific camera pose, then perspective precision is improved, but device complexity increases
Solution Approach 1:
The system segments the continuous space of possible camera poses into a discrete set of predetermined poses for which images are pre-rendered. This segmentation allows the system to manage complexity by working with a finite, manageable set of pre-computed images rather than attempting to render for every possible camera position, while still achieving sufficient perspective precision through selective application and blending of these segmented views.
Data Source
AI summary
The present disclosure relates to a computing device for generating an image configured to be captured by a camera. The computing device being configured to determine an image to be rendered associated with at least one camera pose and then render said image, receive information on a current camera pose, and generate an image associated with the current camera pose based on the rendered image associated with the at least one camera pose.