3D Model Parameterization for Efficient Tessellation
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Solution Overview
Problem
Current CAD systems face inefficiencies in tessellation, particularly with static tessellation consuming excessive memory and time, and PNT tessellation limiting accuracy and causing inaccurate normal vector computation, leading to visualization artifacts.
Innovation Solution
A method for parameterizing a three-dimensional modeled object by determining 2D meshes that fit each face of a boundary representation, allowing for faster and more accurate tessellation with improved memory efficiency and accurate normal vector computation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If static tessellation is used to approximate surfaces with flat triangles, then visualization capability is improved, but memory consumption and processing time increase excessively
Solution Approach 1:
The patent applies preliminary action by pre-computing and storing 2D meshes that fit the parametric surfaces during the parameterization phase. These pre-computed 2D meshes serve as intermediate structures that can be quickly converted to 3D meshes during tessellation, eliminating the need for real-time complex surface approximation calculations and reducing both memory consumption and processing time during visualization.
Solution Approach 2:
The patent introduces 2D meshes as an intermediary structure between the exact parametric surface model and the final 3D tessellation mesh. These 2D meshes act as a mediator that simplifies the tessellation process by providing a pre-organized framework that can be efficiently evaluated and transformed into accurate 3D representations, reducing the computational burden on the system.
2Quantity of substance
If PNT tessellation is used to reduce memory consumption, then memory efficiency is improved, but accuracy decreases and normal vector computation becomes inaccurate
Solution Approach 1:
The patent applies parameter changes by utilizing the associated 2D meshes and their parametric information to dynamically adjust the tessellation accuracy. The system can evaluate the 2D meshes at different levels of detail and compute accurate normal vectors by leveraging the parametric surface definitions, allowing memory-efficient storage while maintaining the ability to achieve any required level of precision when needed.
3Quantity of substance
If PNT tessellation is used to reduce memory consumption, then memory efficiency is improved, but processing time increases
Solution Approach 1:
The patent applies preliminary action by pre-computing and storing 2D meshes during the parameterization phase. These pre-computed structures serve as ready-to-use intermediaries that can be rapidly evaluated and transformed into 3D meshes during tessellation, eliminating the need for time-consuming real-time surface calculations and significantly reducing processing time while maintaining memory efficiency.
4Productivity
If 2D meshes are determined to fit each face, then tessellation speed is improved, but the complexity of the parameterization process increases
Solution Approach 1:
The patent applies segmentation by dividing the parameterization process into distinct stages: first determining 2D meshes that fit each individual face, then using these 2D meshes as intermediaries for the final 3D tessellation. This segmentation allows each stage to be optimized independently, improving overall tessellation speed while managing complexity through modular processing steps.
Data Source
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AI summary
It is proposed a computer-implemented method for parameterizing a three-dimensional modeled object for tessellation. The method comprising the steps of providing (S10) a boundary representation of the modeled object, the boundary representation comprising geometrical data including parametric surfaces and topological data including a set of faces each defined as a portion of the 2D domain of a respective parametric surface; determining (S20) 2D meshes each fitting a respective face; and associating (S30) the 2D meshes to the geometrical data of the boundary representation. Such a solution improves the tessellation of a 3D modeled object.