3D Structure Data Management for Accurate Similarity Search
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Solution Overview
Problem
Existing three-dimensional CAD systems face challenges in accurately reflecting convex and concave features of structures when converting three-dimensional models into graph data for similarity searches, as current methods either include excessive data leading to increased computational costs or fail to capture geometric features effectively.
Innovation Solution
A management apparatus that calculates additional point coordinates based on the spatial arrangement of polygons, using these points to produce graphs that emphasize protrusions and recesses, thereby maintaining geometric features with reduced data size and faster computation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If every edge-to-edge angle is included in graph data to capture convex and concave features, then measurement precision of geometric features is improved, but device complexity and data size increase significantly
Solution Approach 1:
The patent extracts only the essential geometric features (convex and concave points) from the complete set of edge-to-edge angles. Instead of including all angular measurements, it selectively identifies and retains only those points that define the protrusions and recesses of the three-dimensional structure, thereby capturing geometric features without the burden of complete angular data
Solution Approach 2:
The patent applies local quality by treating different regions of the graph data differently. Convex and concave points are identified and given special significance as they locally define the geometric features of the structure. This selective emphasis on specific local characteristics allows accurate geometric representation without requiring uniform detailed data across the entire structure
2Measurement precision
If complete structure data is used for similarity searches, then measurement precision is improved, but productivity of search operations decreases due to increased computational costs
Solution Approach 1:
The patent extracts a simplified representation of the three-dimensional structure by identifying only convex and concave points and their relationships. This extracted subset of data contains the essential information needed for shape comparison while being significantly smaller and faster to process than complete structure data, thereby improving search productivity without sacrificing measurement precision
Solution Approach 2:
The patent segments the complete structure data into distinct geometric features (convex points, concave points, and their relationships). By dividing the complex structure into these meaningful segments, the system can process and compare only the relevant features during similarity searches, reducing computational overhead while maintaining accuracy
Data Source
AI summary
A storage unit stores structure data that includes coordinates of vertices of a plurality of polygons representing a three-dimensional structure. A computation unit calculates coordinates of a certain point with reference to the structure data. This point is used, together with the vertices of the polygons, to produce a graph from the structure data according to spatial arrangement of the polygons and further to calculate characteristic quantities based on the produced graph. The computation unit stores the calculated coordinates of the point in a memory device, as a piece of information relating to the structure data.