Point Cloud Rendering With Clipping Surfaces for Sharp Edges
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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
1Ease of manufacture
If 3D Gaussian splatting is used to represent a scene, then the rendering can be achieved with simple geometric characteristics, but large numbers of Gaussians are required to approximate sharp edges, increasing computational power and memory requirements
Solution Approach 1:
The patent divides the continuous Gaussian extent into discrete regions by introducing clipping surfaces (planes or 3D volumes) that segment the space. Each Gaussian is clipped by these surfaces to render only specific portions, enabling sharp edges without requiring numerous Gaussians. This segmentation approach reduces the total number of Gaussians needed while maintaining rendering quality.
Solution Approach 2:
The patent applies different clipping surfaces to different Gaussians based on their spatial location and the desired image features. By locally adjusting which portions of each Gaussian are rendered, the system efficiently represents sharp edges where needed while maintaining smooth transitions elsewhere, optimizing computational resources.
2Ease of manufacture
If 3D Gaussian splatting is used to represent a scene, then the rendering can be achieved with simple geometric characteristics, but large numbers of Gaussians are required to approximate sharp edges, increasing memory requirements
Solution Approach 1:
The patent introduces clipping surfaces that segment the Gaussian extents into renderable and non-renderable regions. This allows sharp edges to be represented by fewer Gaussians with appropriate clipping planes, reducing the total number of points needed in the point cloud while maintaining edge sharpness.
Solution Approach 2:
The patent extracts and removes portions of Gaussian extents that fall outside the clipping surfaces. By taking out unnecessary portions of the Gaussians, the system reduces the effective number of points contributing to the rendering, improving efficiency without sacrificing image quality.
3Productivity
If clipping surfaces are introduced for each point, then sharp edges can be represented efficiently, but the device complexity increases
Solution Approach 1:
The patent designs clipping surfaces to serve multiple functions: they define sharp edges, control rendering boundaries, and can be reused across multiple Gaussians. This multi-functionality reduces the need for complex per-point processing while maintaining rendering efficiency.
Solution Approach 2:
The patent pre-computes and stores clipping surfaces before rendering. By preparing the clipping geometry in advance, the system avoids complex real-time calculations during rendering, reducing operational complexity while maintaining high rendering efficiency.
Data Source
AI summary
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.