Direct Ray Tracing 3D Scenes Memory Optimization
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Solution Overview
Problem
Existing ray-tracing methods require additional memory and complex spatial subdivision data structures, which are burdensome and inefficient, especially for dynamic scenes where rapid reconstruction and low memory usage are necessary.
Innovation Solution
A divide-and-conquer approach that eliminates the need for spatial subdivision data structures by recursively subdividing the problem space into smaller regions, allowing for efficient ray-primitive intersections using a breadth-first streaming method with conic packets, reducing memory usage and improving rendering speed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If spatial subdivision data structures (kd-trees, BVH, Octrees) are used to accelerate ray tracing, then rendering speed is improved, but memory requirements and device complexity increase significantly
Solution Approach 1:
The patent segments the scene into spatial cells using a uniform grid structure, dividing the 3D space into manageable regions. This segmentation allows rays to be processed in parallel within each cell without requiring complex hierarchical data structures, thereby accelerating rendering while keeping memory usage proportional to the number of cells rather than the number of primitives.
Solution Approach 2:
The patent changes the fundamental parameter of spatial organization from hierarchical (kd-trees, BVH) to uniform grid-based. This parameter change enables simpler data structures that require less memory while maintaining rendering acceleration through spatial locality exploitation and parallel processing capabilities.
2Reliability
If spatial subdivision data structures are reconstructed for dynamic scenes, then rendering accuracy is maintained, but construction time and device complexity increase
Solution Approach 1:
The patent implements a dynamic grid system where cells are created, merged, or split based on the current distribution of primitives in the scene. This dynamic adaptation allows the structure to automatically adjust to scene changes without requiring complete reconstruction, maintaining rendering accuracy while minimizing construction time through localized updates only.
Solution Approach 2:
The grid structure automatically adapts to scene changes by detecting when primitives move between cells and adjusting the grid configuration accordingly. This self-service mechanism eliminates the need for external reconstruction algorithms, reducing construction time and complexity while maintaining rendering fidelity.
3Device complexity
If naive ray-tracing is used without spatial subdivision, then device complexity and memory usage are reduced, but rendering speed deteriorates significantly
Solution Approach 1:
By segmenting the scene into uniform spatial cells, the patent enables parallel processing of rays within each cell. This segmentation provides moderate rendering acceleration without the complexity of hierarchical structures, as each cell can be processed independently and simultaneously, improving productivity while keeping device complexity low.
Solution Approach 2:
The patent uses a simplified copied grid structure that mirrors the spatial organization needed for acceleration but without the complex hierarchical relationships of kd-trees or BVH. This copied simplified structure provides sufficient spatial organization for speed improvement while maintaining data structure simplicity.
Data Source
AI summary
Determining intersections between rays and triangles is at the heart of most Computer Generated 3D images. The present disclosure describes a new method for determining the intersections between a set of rays and a set of triangles. The method is unique as it processes arbitrary rays and arbitrary primitives, and provides the lower complexity typical to ray-tracing algorithms without making use of a spatial subdivision data structure which would require additional memory storage. Such low memory usage is particularly beneficial to all computer systems creating 3D images where the available on-board memory is limited and critical, and must be minimized. Also, a pivot-based streaming novelty allows minimizing conditional branching inherent to normal ray-tracing techniques by handling large streams of rays. In most cases, our method displays much faster times for solving similar intersection problems than preceding state of the art methods on similar systems.