Augmented point cloud for a visualization system and method

Abstract

A visualization system that uses deep learning can store data representing a scene in multiple layers of representation. Each layer can include a different category of data from the other layers. The categories of data can increase in complexity and specificity from a lowermost layer to an uppermost layer. For instance, first, second, and third layers can store information corresponding to edges, corners, and surface finishes present in the scene, respectively. The visualization system can retrieve data representing the scene from multiple layers, and augment a point cloud representation of the scene in response to the retrieved data. The point cloud can be augmented to increase a point density in one or more point cloud regions that lack data or include only sparse data. Downstream, the visualization system can use the augmented point cloud to create improved images of the scene from desired points of view.

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