Sparse Volumetric Rendering for Low-Latency 3D Ray Casting
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Solution Overview
Problem
Current computer vision and graphics systems in augmented and mixed reality face challenges in computational efficiency, particularly in processing high-frame rate 3D data, leading to latency issues that can cause motion sickness and hinder the processing of large volumes within constrained memory and processing resources.
Innovation Solution
A sparse volumetric data structure, such as a sparse sexaquaternary tree format, is used to efficiently represent 3D scenes by tagging voxels as occupied or empty, allowing for reduced storage and faster processing, and is hardware-accelerated to minimize latency in real-time updates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a dense volumetric data structure is used to represent 3D scenes, then complete scene coverage is achieved, but memory consumption and processing time increase significantly
Solution Approach 1:
The volumetric space is divided into a hierarchical octree structure where the volume is recursively subdivided into smaller voxels. This segmentation allows the system to represent only the necessary portions of space at appropriate levels of detail, reducing overall memory consumption while maintaining complete scene coverage through the hierarchical organization of occupied and empty spaces.
Solution Approach 2:
Different regions of the volumetric scene are represented at different levels of detail based on their occupancy characteristics. Occupied voxels are stored with full detail while empty voxels are represented more compactly or omitted entirely. This local quality approach ensures that memory resources are allocated efficiently to regions that require detailed representation while using minimal resources for empty spaces.
2Productivity
If high-frame rate 3D data processing is implemented, then real-time rendering is achieved, but computational load and latency increase
Solution Approach 1:
The system performs preliminary processing by pre-computing and storing occupancy information in the hierarchical octree structure before rendering operations. This preliminary organization of spatial data allows subsequent frame rendering to proceed more quickly by eliminating the need for on-the-fly spatial computations, thereby reducing latency while maintaining high frame rates.
Solution Approach 2:
The volumetric data structure dynamically adapts its representation based on scene changes and viewing requirements. The hierarchical octree allows the system to adjust the level of detail and processing focus dynamically, concentrating computational resources on regions that have changed or are currently visible, thus achieving real-time performance with reduced overall computational load.
3Quantity of substance
If a compact voxel octree data structure is used for ray-casting, then memory efficiency is improved, but ray-voxel intersection detection complexity increases
Solution Approach 1:
The ray-casting algorithm leverages the segmented hierarchical octree structure by traversing the tree levels systematically. Instead of checking all voxels in the volume, the algorithm segments the search space by following the hierarchical decomposition, only examining occupied voxels at each level. This segmentation approach maintains memory efficiency while reducing the actual computational work required for ray-voxel intersection detection.
4Productivity
If sparse volumetric representation is used to reduce data storage, then processing speed improves, but rendering accuracy may be compromised
Solution Approach 1:
The system dynamically adjusts the level of detail in the sparse volumetric representation based on the specific rendering operation and viewing parameters. For operations requiring high precision, the system accesses lower-level voxels in the hierarchy that provide finer detail. For operations where approximate results suffice, higher-level coarse representations are used. This dynamic adaptation maintains processing speed while preserving rendering accuracy when needed.
Data Source
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AI summary
A ray is cast into a volume described by a volumetric data structure, which describes the volume at a plurality of levels of detail. A first entry in the volumetric data structure includes a first set of bits representing voxels at a lowest one of the plurality of levels of detail, and values of the first set of bits indicate whether a corresponding one of the voxels is at least partially occupied by respective geometry. A set of second entries in the volumetric data structure describe voxels at a second level of detail, which represent subvolumes of the voxels at the first lowest level of detail. The ray is determined to pass through a particular subset of the voxels at the first level of detail and at least a particular one of the particular subset of voxels is determined to be occupied by geometry.