Neural Scene Representation for Faster Photorealistic 2D Rendering
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for simulating real-world camera imaging, such as ray tracing, require determining all physical parameters of a scene, including geometry and material properties, which can be computationally intensive and inefficient for generating photorealistic images.
Innovation Solution
An electronic device uses a processor to generate point information and pixel information in a 3D space based on factor data, employing neural scene representation (NSR) data to compress and factorize the 3D space into tensor sets, allowing for parallel processing of color and volume density calculations to create 2D images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If ray tracing techniques are used to generate photorealistic images by simulating light propagation and determining all physical parameters of a scene, then image quality is improved, but computational complexity and processing time increase
Solution Approach 1:
The patent segments the scene representation into discrete voxels arranged in a 3D grid structure. Each voxel contains pre-computed lighting and material properties, dividing the complex continuous scene into manageable discrete units that can be processed and stored efficiently
Solution Approach 2:
The patent performs preliminary computation of lighting, shading, and material properties for each voxel during an offline preprocessing stage. This pre-computation stores complex physical parameters in advance, eliminating the need for real-time ray tracing calculations when generating images from the voxel scene representation
2Manufacturing precision
If all physical parameters of a scene are determined in a rendering process including geometry and material properties, then photorealistic quality is achieved, but data quantity and processing requirements increase
Solution Approach 1:
The patent transforms the scene representation from continuous geometric and material parameters into discrete voxel-based parameters with fixed resolution. By changing the representation format and pre-computing parameters at specific resolution levels, the patent reduces the overall data quantity while preserving photorealistic quality characteristics
3Productivity
If neural scene representation data is used to compress and factorize 3D space into tensor sets, then processing speed is improved, but data structure complexity increases
Solution Approach 1:
The patent creates a simplified copy of the 3D scene in the form of a voxel grid representation. This voxel copy captures the essential scene properties in a structured format that enables faster processing compared to the original complex scene data, while maintaining the necessary information for image generation
Data Source
Figure 1
Figure 2
Figure 3
AI summary
A device including a processor configured to generate, for each of plural query inputs, point information using factors individually extracted from a plurality of pieces of factor data for a corresponding query input and generate pixel information of a pixel position using the point information of points, the plural query inputs being of the points, in a 3D space, on a view direction from a viewpoint toward a pixel position of a two-dimensional (2D) scene.