Voxelization of 3D Mesh via GPU Interpolation
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Solution Overview
Problem
Existing image manipulation technologies face challenges in handling high-resolution images with a large number of colors in time-critical fields, often requiring reduced image quality or increased processing time to maintain real-time behavior.
Innovation Solution
A method involving a dedicated graphics processor that transforms 3D triangles into 2D triangles with interpolatable pixel attributes, allowing for efficient interpolation and rendering of high-resolution images by converting pixel attributes into voxel coordinates, thereby leveraging the parallel processing capabilities to manage complex image manipulations in real-time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If image resolution and color depth are increased to improve image quality, then image quality is improved, but processing time increases and real-time manipulation becomes difficult
Solution Approach 1:
The patent replaces traditional CPU-based image processing with GPU-based parallel processing. The graphics processor uses vertex shaders and pixel shaders to perform simultaneous calculations on multiple pixels and vertices, substituting sequential mechanical processing with parallel graphical processing architecture designed for high-throughput image manipulation.
Solution Approach 2:
The patent segments the image processing task into discrete vertex operations and pixel operations. Vertices are processed independently to define triangle geometry, while pixels within each triangle are processed through interpolation and blending operations. This segmentation allows the GPU to process different parts of the image simultaneously across multiple cores.
2Productivity
If traditional CPU-based processing is used for high-resolution images, then processing flexibility is maintained, but processing speed decreases and real-time performance cannot be achieved
Solution Approach 1:
The patent substitutes the traditional CPU processing architecture with a GPU architecture optimized for parallel image processing. The graphics processor contains multiple vertex processing units and pixel processing units that can simultaneously handle thousands of operations, achieving real-time performance for high-resolution images despite increased architectural complexity.
Solution Approach 2:
The patent leverages the universal nature of graphics processors that can handle multiple image processing tasks through programmable shaders. The same GPU hardware can perform vertex transformation, pixel interpolation, blending, and various image manipulation operations by loading different shader programs, providing both speed and flexibility.
Data Source
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AI summary
A method for 3D rendering, including receiving a group of 3D triangles defining a mesh of a surface, each 3D triangle in the group having 3D vertices with respective 3D coordinates, and transforming each 3D triangle into a 2D triangle having 2D vertices corresponding respectively to the 3D vertices, each 2D vertex having respective 2D pixel coordinates and a triplet of pixel attributes corresponding to the 3D coordinates of a corresponding 3D vertex. Each 2D triangle is passed to a graphics processor, which treats the triplet of pixel attributes of each 2D vertex as interpolatable values. The graphics processor computes respective triplets of interpolated pixel attributes for pixels within each 2D triangle by interpolation between the pixel attributes of the 2D vertices, and a 3D image of the surface is rendered by converting the interpolated pixel attributes computed by the graphics processor into voxel coordinates in the 3D image.