Intel corporation (20240320782). Apparatus and Method for Density-Aware Stochastic Subsets for Improved Importance Sampling simplified abstract
Contents
Apparatus and Method for Density-Aware Stochastic Subsets for Improved Importance Sampling
Organization Name
Inventor(s)
Lorenzo Tessari of Baden Wuerttemberg (DE)
Apparatus and Method for Density-Aware Stochastic Subsets for Improved Importance Sampling - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240320782 titled 'Apparatus and Method for Density-Aware Stochastic Subsets for Improved Importance Sampling
Simplified Explanation: The patent application describes an apparatus and method for density-aware stochastic subsets to enhance importance sampling. It involves generating sampling weights for input primitives based on their surface area and distances to neighboring primitives, identifying a representative subset of primitives, constructing a bounding volume hierarchy (BVH) based on this subset, and building a final BVH with all input primitives.
- Sampling weight generator determines weights for input primitives based on surface area and distances to neighbors.
- Sampler identifies a representative subset of input primitives using the sampling weights.
- BVH builder hardware logic constructs an approximate BVH based on the representative subset.
- Hardware logic inserts input primitives not in the subset into leaves of the approximate BVH.
- Final BVH is constructed based on the primitives inserted into the leaves of the approximate BVH.
Potential Applications: This technology can be applied in computer graphics, ray tracing, virtual reality, and simulation software to improve sampling efficiency and accuracy.
Problems Solved: The technology addresses the challenge of efficiently selecting representative subsets of input primitives for importance sampling in complex computational tasks.
Benefits: - Enhanced sampling efficiency - Improved accuracy in computational tasks - Better utilization of computational resources
Commercial Applications: Density-aware stochastic subsets can be utilized in industries such as animation studios, video game development, scientific simulations, and architectural visualization software to optimize rendering processes and enhance visual quality.
Prior Art: Prior research in importance sampling techniques and BVH construction methods can provide valuable insights into the development of this technology.
Frequently Updated Research: Researchers are constantly exploring new algorithms and optimizations for importance sampling and BVH construction in computer graphics and simulation fields.
Questions about Density-Aware Stochastic Subsets: 1. How does this technology improve sampling efficiency in computational tasks? 2. What are the potential applications of density-aware stochastic subsets beyond computer graphics and simulation software?
Original Abstract Submitted
apparatus and method for density-aware stochastic subsets for improved importance sampling. for example, one embodiment of an apparatus comprises: a sampling weight generator to determine a plurality of sampling weights associated with a corresponding plurality of input primitives, the sampling weight generator to determine each sampling weight based on a surface area or diagonal of a bounding box of the corresponding input primitive and a plurality of distance values corresponding to distances between the input primitive and a corresponding plurality of neighboring input primitives; a sampler to identify a representative subset of the input primitives based, at least in part, on the plurality of sampling weights; bounding volume hierarchy (bvh) builder hardware logic to construct an approximate bvh based on the representative subset of input primitives; hardware logic to insert input primitives not in the representative subset into leaves of the approximate bvh; and the bvh builder or a different bvh builder to construct a final bvh based on the primitives inserted into the leaves of the approximate bvh.
