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METHODS AND SYSTEMS FOR GENERATING 3D DATASETS TO TRAIN DEEP LEARNING NETWORKS FOR MEASUREMENTS ESTIMATION
METHODS AND SYSTEMS FOR GENERATING 3D DATASETS TO TRAIN DEEP LEARNING NETWORKS FOR MEASUREMENTS ESTIMATION
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机译:用于生成3D数据集以培训深度学习网络进行测量估计的方法和系统
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摘要
Disclosed are systems and methods for generating data sets for training deep learning networks for key point annotations and measurements extraction from photos taken using a mobile device camera. The method includes the steps of receiving a 3D scan model of a 3D object or subject captured from a 3D scanner and a 2D photograph of the same 3D object or subject at a virtual workspace. The 3D scan model is rigged with one or more key points. A superimposed image of a pose-adjusted and aligned 3D scan model superimposed over the 2D photograph is captured by a virtual camera in the virtual workspace. Training data for a key point annotation DLN is generated by repeating the steps for a plurality of objects belonging to a plurality of object categories. The key point annotation DLN learns from the training data to produce key point annotations of objects from 2D photographs captured using any mobile device camera.
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