Point Cloud Mesh Refinement for 3D Printing Shape and Color
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Solution Overview
Problem
Existing 3D printing systems struggle to efficiently convert point clouds into printable files while maintaining shape, volume, and color information, as they often require large amounts of computational resources and fail to accurately represent attributes of spaces or volumes inside the mesh.
Innovation Solution
A method that combines computational geometry and field approaches to derive a watertight alpha shape mesh from point clouds, using normal vectors and signed distance fields to refine the mesh, thereby reducing computational resources and improving accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If a mesh is used to represent point cloud data for 3D printing, then the shape and volume information can be defined, but a very large amount of information needs to be generated, stored and processed
Solution Approach 1:
The patent extracts only the essential geometric information needed for 3D printing from the point cloud, rather than processing the entire point cloud or creating a complete mesh. This is achieved by identifying and processing only the boundary points that define the object's exterior surface, thereby reducing the amount of data that needs to be generated, stored, and processed while maintaining accurate shape and volume representation.
Solution Approach 2:
The patent segments the point cloud data by separating boundary points from internal points. The method identifies points that lie on the exterior surface of the object and processes only these boundary points to generate the 3D model, leaving internal points to be handled differently or excluded. This segmentation significantly reduces computational complexity while preserving the essential geometric features needed for manufacturing.
2Manufacturing precision
If a mesh is used to represent point cloud data, then points on the mesh can be defined, but attributes of spaces or volumes inside the mesh cannot be represented
Solution Approach 1:
The patent transitions from representing only surface geometry (2D mesh) to incorporating volume information by processing points in three-dimensional space. By using spatial relationships and distance calculations in 3D, the method can determine which points are inside or outside the object's boundary, thereby preserving information about internal spaces and volumes that would be lost in a traditional mesh representation.
3Reliability
If traditional mesh methods are used to convert point clouds, then a complete surface model can be created, but computational resources are excessively consumed
Solution Approach 1:
The patent applies partial action by processing only the necessary subset of points required to create an accurate 3D printing model. Instead of processing all points in the point cloud or generating a complete high-resolution mesh, the method processes only the boundary points that are essential for defining the object's exterior surface. This partial processing approach maintains model completeness for printing purposes while dramatically improving processing efficiency.
Data Source
Figure 1A
Figure 1B~2
Figure 3A~3B
AI summary
Methods and systems are provided, which convert points in a cloud into a model for 3D printing in a computationally efficient manner and while maintaining and possibly adjusting shape, volume and color information. Methods include deriving, from the points, a crude watertight mesh with respect to the points, e.g., an alpha shape, determining, using normal vectors associated with the points, locations of the points with respect to the mesh (e.g., as being inside, outside or within the model) and using the derived mesh to define the model with respect to the determined locations of the points. Combining the computational geometry approach with the field approach is synergetic and results in better information content of the resulting model for 3D printing while consuming less computational resources.