3D Surface Shape Generation from Point Cloud Data
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Solution Overview
Problem
Conventional three-dimensional scanners face difficulties in accurately converting point cloud data into three-dimensional shape data, particularly with free curved surfaces, leading to surface deformation or missing surfaces due to elemental shapes like holes and dents, which increases operator workload.
Innovation Solution
A computer program product that acquires point cloud data, designates and removes locally changing element shapes, generates complementary data, and synthesizes three-dimensional CAD model data to maintain surface continuity, allowing for accurate conversion into surface or solid models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional three-dimensional scanning is used to generate point cloud data, then three-dimensional coordinates of surface positions can be obtained, but surface deformation and missing surfaces occur during conversion to three-dimensional shape data, especially with free curved surfaces and elemental shapes like holes and dents
Solution Approach 1:
The patent segments the three-dimensional shape data into multiple patches, where each patch is independently processed to maintain surface continuity. This segmentation allows the system to handle complex surfaces with holes and dents by treating them as separate manageable units that can be individually fitted and then seamlessly combined.
Solution Approach 2:
The patent applies preliminary actions by pre-processing the point cloud data to identify and classify elemental shapes (holes, dents, protrusions) before generating the three-dimensional shape data. This preliminary classification enables the system to apply appropriate fitting methods for each element type, preventing surface deformation during conversion.
2Adaptability or versatility
If free curved surface shape is used to convert point cloud data to three-dimensional shape data, then surface flexibility is improved, but data conversion fails for holes and dents, increasing operator workload for correction
Solution Approach 1:
The patent implements self-service by enabling the system to automatically detect, classify, and process elemental shapes (holes, dents, protrusions) without operator intervention. The system autonomously fits appropriate geometric models to these features and integrates them into the three-dimensional shape data, eliminating the need for manual correction and significantly reducing operator workload.
Solution Approach 2:
The patent changes parameters by dynamically adjusting the complexity and type of geometric fitting based on the detected elemental shape characteristics. For simple surfaces, basic fitting methods are used, while for complex features like holes and dents, the system automatically switches to more sophisticated parametric models, optimizing both accuracy and processing efficiency.
3Productivity
If conventional data conversion methods are used, then processing speed is maintained, but surface deformation occurs leading to failed data conversion and increased correction time
Solution Approach 1:
The patent performs preliminary classification of point cloud data to identify elemental shapes and surface characteristics before the main conversion process. This pre-processing step organizes the data into structured groups that can be efficiently processed, maintaining high conversion speed while ensuring reliable results by applying appropriate fitting methods to each element type.
Solution Approach 2:
The patent segments the conversion process into parallel processing streams for different element types (holes, dents, protrusions, regular surfaces). This segmentation allows simultaneous processing of multiple surface features, maintaining high productivity while improving reliability through specialized handling of each element type, thereby preventing surface deformation.
Data Source
AI summary
A computer program product including programmed instructions that cause a computer to perform acquiring, changing, first generating, second generating, and synthesizing. The acquiring includes acquiring first point cloud data including a position on a first three-dimensional surface shape. The changing includes changing, using a three-dimensional element shape, the first three-dimensional surface shape represented by the first point cloud data to a second three-dimensional surface shape. The first generating includes generating second point cloud data including a surface position on the second three-dimensional surface shape. The second generating includes generating, from the second point cloud data, second shape data representing the second three-dimensional shape. The synthesizing includes synthesizing element shape data of the surface model or the solid model and the second shape data to generate first shape data representing the surface model or the solid model of the first three-dimensional shape.