Ensuring a smooth user experience in a multi-user augmented reality system

A computer program product for improving operational performance of a multi-user augmented reality system, the computer program product comprising one or more computer readable storage mediums having program code embodied therewith, the program code comprising programming instructions of a computer-implemented method of comprising:

• transforming a first image with a virtual three-dimensional object into a first quadtree data structure;
• sharing said first quadtree data structure with a second computing device which is inputted into a machine learning model on said second computing device to obtain a first machine learning result which is used by said second computing device to render a second image of said virtual three-dimensional object;
• receiving said second image as a second quadtree data structure as well as said first machine learning result from said second computing device;
• inputting said second quadtree data structure and said first machine learning result into a machine learning model on a first computing device to obtain a second machine learning result which includes correction values for modifying said first image;
• and
• updating a rendering of said first image using said correction values.

A system, comprising:

• a memory for storing a computer program for improving operational performance of a multi-user augmented reality system;
• and
• a processor connected to the memory, wherein the processor is configured to execute program instructions of the computer program of a computer-implemented method comprising:
• transforming a first image with a virtual three-dimensional object into a first quadtree data structure;
• sharing said first quadtree data structure with a second computing device which is inputted into a machine learning model on said second computing device to obtain a first machine learning result which is used by said second computing device to render a second image of said virtual three-dimensional object;
• receiving said second image as a second quadtree data structure as well as said first machine learning result from said second computing device;
• inputting said second quadtree data structure and said first machine learning result into a machine learning model on a first computing device to obtain a second machine learning result which includes correction values for modifying said first image;
• and
• updating a rendering of said first image using said correction values.