Discontinuity-Aware Late Stage Reprojection for VR Stereoscopic Accuracy
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Solution Overview
Problem
Conventional methods for rendering virtual reality scenes face challenges in maintaining true stereoscopy and handling dis-occlusions due to latency in communication media and inefficiencies in processing and caching large image data, particularly in providing accurate stereoscopic views.
Innovation Solution
The implementation of a reprojection engine that performs optimized late-stage reprojection based on discontinuity and depth awareness, using a depth-aware cube map late stage reprojection operation to reconstruct stereoscopic views in real-time by processing sparse sample points, thereby resolving dis-occlusions and improving user experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional rendering methods are used to maintain true stereoscopy, then stereoscopic accuracy is improved, but processing time and latency increase
Solution Approach 1:
The patent segments the virtual scene into multiple depth layers or planes, allowing independent processing of each layer. This segmentation enables parallel processing operations that reduce overall latency while maintaining stereoscopic accuracy, as each layer can be rendered and processed separately rather than requiring complete scene re-rendering.
Solution Approach 2:
The patent performs preliminary depth estimation and layer segmentation during the rendering process, preparing depth maps and layer structures in advance. This preliminary action allows the reprojection system to quickly adjust stereoscopic views without requiring complete re-rendering, thus reducing processing latency while maintaining accuracy.
2Manufacturing precision
If complete virtual scene data is processed and cached, then rendering accuracy is improved, but memory usage and processing overhead increase
Solution Approach 1:
The patent extracts only the essential depth information and layer structures from complete scene data, storing compressed depth maps and layer metadata instead of full scene geometry. This extraction approach maintains rendering accuracy by preserving critical depth relationships while dramatically reducing memory requirements compared to storing complete virtual scene data.
Solution Approach 2:
The patent applies different levels of data detail to different regions of the scene based on their importance and visibility. Critical areas with complex geometry receive higher fidelity depth mapping, while less important areas use compressed representations. This local quality approach maintains overall rendering accuracy while reducing total memory usage by allocating storage resources efficiently.
3Measurement precision
If real-time reprojection is performed using traditional methods, then stereoscopic view accuracy is improved, but power consumption increases
Solution Approach 1:
The patent performs partial reprojection operations, updating only the portions of the scene that require stereoscopic adjustment rather than complete scene re-rendering. By applying reprojection transformations selectively to specific depth layers and regions, the system maintains stereoscopic view accuracy while significantly reducing the computational power required compared to traditional full-scene reprojection methods.
Data Source
AI summary
In various embodiments, methods and systems reprojecting three-dimensional (3D) virtual scenes using discontinuity depth late stage reprojection are provided. A reconstruction point, that indicates camera pose information, is accessed. The reconstruction point is associated with a plurality of sample points of a three-dimensional (3D) virtual scene. One or more closest sample points, relative to the reconstruction point, are identified, from the plurality of sample points. Each of the one or more closest sample points is associated with a cube map of color data and depth data. A relative convergence score is determined for each of the one or more closest sample points based on performing a depth-aware cube map late stage reprojection operation in relation to the reconstruction point. A subset of the one or more closest sample points is identified based on the relative convergence score. A reconstructed 3D virtual image is generated using the subset.