Machine learning-based geometric mesh simplification

Abstract

Techniques of simplifying triangular meshes involve performing machine learning on triangle mesh data to produce simplified triangle mesh data representing a simplified triangle mesh having a specified number of triangles. Along these lines, a computer obtains triangular mesh data representing a triangular mesh that approximates an object. For example, a triangular mesh that provides a very good approximation of a human head may have tens or hundreds of thousands of triangular faces and vertices. The computer then inputs this triangular mesh data and a specified number of triangular faces into a machine learning application. The specified number of triangular faces is much less than the number of faces in the triangular mesh data input into the machine learning application. The machine learning application, having been trained on multiple sets of triangular mesh/simplified triangular mesh data pairs, outputs simplified triangular mesh data representing a simplified triangular mesh having the specified number of sides.