Disclosed are various embodiments for inferring quality in point cloud-based three-dimensional objects using topographical data analysis. A first graph is generated representing a three-dimensional model, each vertex in the first graph representing a respective connected component within a layer of the three-dimensional model and each edge in the first graph representing a connection between two respective connected components within two respective layers of the three-dimensional model. A second graph representing negative space associated with the three-dimensional model is also generated, each vertex in the second graph representing a connected component of a negative space region within the layer of the three-dimensional model and each edge in the second graph representing a connection between two respective connected components with two respective layers of the three-dimensional model. A persistent homology analysis is applied to the first graph to determine whether a hole or tunnel exists in each vertex of the first graph. An error with the three-dimensional model can then be identified based at least in part on the first graph, the second graph, and the persistent homology analysis.USF inventors have developed various techniques to infer the quality of point cloud-based 3D objects using topographical data analysis (TDA). A tool called Mapper is used to extract topological information about the layer-by-layer connectivity. Persistent homology is used for the detection of connected components and holes within a printer layer. Together these tools are used to analyze both the printed space and empty space created by the model. The invention enables the users to investigate print qualities of the model and identify potential anomalies like connectedness, watertightness, and holes/tunnels in the printed model that appear in the final product before it is physically made. This helps to reduce misprints, saving printer time and money wasted on material.
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