3D Print Model Generation via Hidden Point Removal
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Solution Overview
Problem
3D printing of virtual game environments faces challenges due to intersecting elements creating closed voids when exported from virtual space to physical models, which can trap printing material and result in unbalanced or costly models, and existing methods struggle to automate the selection of elements for printing.
Innovation Solution
A system and method involving an entertainment device coupled with a 3D printer, utilizing point cloud sampling and hidden point removal techniques to generate a surface-only point cloud, which is then rendered as voxels to create a 3D model that excludes internal features, ensuring only visible surfaces are printed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If virtual environment elements are exported for 3D printing, then a physical model can be created, but intersecting elements create closed voids that trap printing material
Solution Approach 1:
The patent extracts and removes hidden points from the point cloud data before generating the 3D printing model. By identifying and eliminating points that are not visible from any external viewpoint, the system prevents the formation of closed voids that would trap printing material, while preserving all externally visible surfaces.
Solution Approach 2:
The patent performs hidden point removal as a preliminary step before exporting the model for 3D printing. By processing the point cloud data in advance to eliminate internal features, the system prepares a clean model that avoids material entrapment issues during the actual printing process.
2Manufacturing precision
If all elements including internal features are printed, then complete model accuracy is achieved, but printing cost and material usage increase
Solution Approach 1:
The patent extracts only the externally visible surfaces from the complete model by removing hidden points. This selective extraction maintains the visual and structural accuracy of the model as it would appear from the outside, while eliminating the need to print internal features that would consume unnecessary material.
Solution Approach 2:
The patent applies different processing quality to different parts of the model: externally visible surfaces are preserved with high fidelity, while internal hidden features are removed. This local differentiation optimizes material usage by printing only where necessary for visual accuracy.
3Productivity
If automated selection of printable elements is implemented, then efficiency improves, but complexity of the system increases
Solution Approach 1:
The patent implements a self-service automated system where the point cloud data structure itself enables identification of visible versus hidden points through mathematical analysis. The system uses the inherent geometric properties of the point cloud and viewing ray intersections to automatically determine which points should be printed, without requiring complex manual intervention or additional hardware.
Data Source
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AI summary
A method of generating a model for 3D printing, comprises selecting a target object within a virtual environment; sampling the target object to form a point cloud, the point cloud comprising points corresponding to an outer surface of the target object and also one or more internal features of the target object; rendering the point cloud from a plurality of viewpoints using voxels in place of the points in the point cloud; detecting which voxels and hence which points of the cloud were rendered over the plurality of renders; forming a surface-only point cloud comprising those points of the cloud that were rendered; and generating a model for 3D printing based on the surface-only point cloud.