Point Cloud Extent Clipping for Sharp-Edge Rendering
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Solution Overview
Problem
Existing 3D Gaussian splatting techniques require large computational power and memory to represent discontinuous or sharp edges due to their inherent geometric characteristics, necessitating a more efficient method for rendering point clouds.
Innovation Solution
Implementing a clipping surface for each point in the point cloud, which can be a plane or a 3D volume, to define the boundary of the extent, allowing for the efficient representation of sharp edges by selectively rendering portions of the extent.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If 3D Gaussian splatting is used to represent a scene, then rendering capability is improved, but computational power and memory requirements increase significantly to represent sharp edges
Solution Approach 1:
The patent divides the continuous Gaussian extent into discrete segments by introducing clipping surfaces (planes or 3D volumes) that partition the space. Each clipping surface independently defines a region where the Gaussian function is evaluated, allowing the system to represent sharp edges by combining a limited number of clipped regions rather than using numerous overlapping Gaussians, thus reducing computational requirements while maintaining rendering quality.
2Manufacturing precision
If large numbers of Gaussians are used to approximate an edge, then edge representation accuracy is improved, but computational complexity and memory usage increase
Solution Approach 1:
The patent introduces clipping surfaces as intermediary structures between the Gaussian functions and the final rendered image. These clipping surfaces act as mediators that define precise boundary conditions, allowing the system to achieve accurate edge representation by evaluating Gaussian functions within constrained regions rather than by increasing the number of Gaussians. The clipping surfaces carry the edge information, reducing the computational burden on the Gaussian rendering process.
Data Source
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AI summary
There is provided a computer-implemented method of rendering an image using a point cloud, the method comprising: receiving a plurality of points in the point cloud, each point comprising an extent defined by a three-dimensional extent function, centred on a centre point; determining a clipping surface for a point within the point cloud, wherein the clipping surface defines a boundary of the extent; and rendering the image by rendering a portion of the extent of each point within the boundary defined by its respective clipping surface.