Angle-Weighted Normals for Geometry Classification
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Solution Overview
Problem
Current methods for creating models of objects with complex surfaces or performing fracture operations in special effects, such as constructive solid geometry, face challenges in accurately classifying faces during intersection, leading to potential errors and manual corrections required by artists.
Innovation Solution
A method involving the classification of geometry portions based on angle-weighted normals and flood-fill algorithms to determine faces above or below a cutting surface, reducing errors and automating the fracture process in virtual environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional classification methods are used during geometry intersection, then the process is simpler, but classification accuracy deteriorates leading to errors requiring manual corrections
Solution Approach 1:
The patent segments the classification process into multiple stages: initial classification of clearly identifiable faces, identification of ambiguous faces that require further processing, and iterative resolution of ambiguities through neighbor relationship analysis. This segmentation allows complex classification to be broken down into manageable steps, improving accuracy without overwhelming system complexity.
Solution Approach 2:
The patent performs preliminary classification of faces that can be confidently classified before intersection operations, establishing a foundation of known correct classifications. This preliminary action provides reference points that guide the subsequent resolution of ambiguous cases, reducing the overall complexity of the classification task.
2Reliability
If manual corrections are performed to fix classification errors, then accuracy improves, but productivity deteriorates due to time-consuming manual intervention
Solution Approach 1:
The patent implements a self-service classification system where ambiguous faces automatically resolve their own classification status by analyzing their spatial relationships with already-classified neighbor faces. This automated self-resolution eliminates the need for manual intervention in most cases, maintaining high reliability while preserving productivity.
Solution Approach 2:
The system uses feedback from classified faces to resolve ambiguities in unclassified faces. The classification status of neighbor faces provides feedback that propagates through the geometry, automatically correcting potential errors and reinforcing accurate classifications without requiring manual review.
3Adaptability or versatility
If complex surface models are created using CSG, then modeling capability improves, but the complexity of surface intersection and classification increases
Solution Approach 1:
The patent segments the complex surface geometry into discrete faces and edges that can be individually classified and processed. This segmentation allows CSG operations to be applied systematically to complex surfaces by breaking them down into manageable classification units, maintaining versatility while controlling processing complexity.
Solution Approach 2:
The patent applies different classification strategies to different regions of the geometry based on local characteristics. Faces with clear spatial relationships receive standard classification, while faces in ambiguous regions receive specialized processing based on their local neighbor relationships, optimizing the balance between capability and complexity.
Data Source
AI summary
A first geometry and a second geometry are accessed. They are positioned so that the first geometry and the second geometry at least in part intersect. The first geometry is divided into portions based on the intersection with the second geometry. At least a first portion of the first geometry is classified as being on one side of the second geometry. At least a second portion of the first geometry is classified as being on another side of the second geometry. At least a third portion of the first geometry is unclassified. The classifying includes comparing an angle weighted normal of a face with a property of the second geometry. The third portion is reclassified as either above the second geometry or below the second geometry according to the classification of a neighboring portion.