Patent Document ID: 20170085863
Application ID: 14967939
Patent Status: 0

Claim One:
1. A machine learning method of converting 2D video to 3D video, comprising: obtaining a training set comprising a plurality of conversion examples, each conversion example comprising a 2D scene example comprising one or more 2D frame examples; a corresponding 3D conversion dataset example that describes conversion of said 2D scene example to 3D, comprising inputs and outputs for 2D to 3D conversion steps, said 2D to 3D conversion steps comprising obtaining one or more 2D frames; locating and identifying an object in one or more object frames within said one or more 2D frames, each object frame containing an image of at least a portion of said object; generating an object mask for said object in said one or more object frames, said object mask identifying one or more masked pixels representing said object in said one or more object frames; generating an object depth model that assigns a pixel depth to one or more of said one or more masked pixels; generating a stereoscopic image pair for each of said one or more object frames based on said object depth model, said stereoscopic image pair comprising a left image and a right image; and, generating one or more gap filling pixel values for one or more missing pixels in said left image or in said right image; training a machine learning system on said training set; obtaining a 2D video; applying said machine learning system to said 2D video to perform one or more of said 2D to 3D conversion steps on said 2D video; and, accepting input from an operator to modify or complete one or more of said 2D to 3D conversion steps on said 2D video.