Invention Grant
- Patent Title: Methods and systems for generating 3D datasets to train deep learning networks for measurements estimation
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Application No.: US17773661Application Date: 2020-11-02
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Publication No.: US11798299B2Publication Date: 2023-10-24
- Inventor: Kyohei Kamiyama , Chong Jin Koh
- Applicant: Bodygram, Inc.
- Applicant Address: US NY New York
- Assignee: Bodygram, Inc.
- Current Assignee: Bodygram, Inc.
- Current Assignee Address: US NY New York
- Agency: American Patent Agency PC
- Agent Daniar Hussain; Stephen M. Hou
- International Application: PCT/US2020/058457 2020.11.02
- International Announcement: WO2021/087425A 2021.05.06
- Date entered country: 2022-05-02
- Main IPC: G06T7/00
- IPC: G06T7/00 ; G06V20/64 ; G06T7/33 ; G06T7/73 ; G06N3/08 ; G06V10/20 ; G06V40/10

Abstract:
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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