Methods and systems for automatic generation of massive training data sets from 3d models for training deep learning networks

Abstract

Disclosed are systems and methods for generating large data sets for training deep learning networks for 3D measurements extraction from images taken using a mobile device camera. The method includes the steps of receiving at least one 3D model; generating a first type of augmentation data, such as but not limited to skin color, face contour, hair style, virtual clothing, and/or lighting conditions; augmenting the 3D model with the first type of augmentation data; generating at least one image from the augmented 3D model; receiving a second type of augmentation data, such as a plurality of background images representing a variety of backgrounds; augmenting the at least one image with the second type of augmentation data to generate a plurality of augmented images; extracting spatial features from the 3D model; and providing the plurality of augmented images and the spatial features to train a deep learning network for 3D measurement determination.