Microsoft Corporation
Three-dimensional map inconsistency detection using neural network

Last updated:

Abstract:

A three-dimensional (3D) map inconsistency detection machine includes an input transformation layer connected to a neural network. The input transformation layer is configured to 1) receive a test 3D map including 3D map data modeling a physical entity, 2) transform the 3D map data into a set of 2D images collectively corresponding to volumes of view frustums of a plurality of virtual camera views of the physical entity modeled by the test 3D map, and 3) output the set of 2D images to the neural network. The neural network is configured to output an inconsistency value indicating a degree to which the test 3D map includes inconsistencies based on analysis of the set of 2D images collectively corresponding to the volumes of the view frustums of the plurality of virtual camera views.

Status:
Grant
Type:

Utility

Filling date:

9 Jun 2020

Issue date:

10 May 2022