Inferring Quality In Point Cloud-Based 3D Printed Objects Using Topological Data Analysis
Assessing the quality of 3D printed models before they are printed remains a challenging problem, particularly when considering point cloud based models. This paper introduces an approach to quality assessment, which uses techniques from the field of Topological Data Analysis to compute a topological abstraction of the eventual printed model. This abstraction enables investigating certain qualities of the model, with respect to print quality, and identify potential anomalies that may appear in the final product.
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