Invention Grant
- Patent Title: Method to generate neural network training image annotations
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Application No.: US16888418Application Date: 2020-05-29
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Publication No.: US11335007B2Publication Date: 2022-05-17
- Inventor: Duanfeng He , Vincent J. Daempfle
- Applicant: ZEBRA TECHNOLOGIES CORPORATION
- Applicant Address: US IL Lincolnshire
- Assignee: ZEBRA TECHNOLOGIES CORPORATION
- Current Assignee: ZEBRA TECHNOLOGIES CORPORATION
- Current Assignee Address: US IL Lincolnshire
- Agent Yuri Astvatsaturov
- Main IPC: G06T7/55
- IPC: G06T7/55 ; G06T7/194 ; G06N3/08 ; G06V40/10

Abstract:
A method of generating neural network training image annotations includes training a first neural network to identify and segment hands in images using a first set of 2D images with hand portions segmented in each image; substantially simultaneously capturing both a second set of 2D images, and a third set of images including depth images, depicting hands holding a particular type of object; correlating each of the second set of images with corresponding images of the third set to identify and segment foregrounds from backgrounds in the second set of images; applying the trained first neural network to the identified foregrounds to identify hand portions of the foregrounds and segment object portions from identified hand portions; and training a second neural network, using the segmented object portions of the second set of images as training data, to identify the particular type of object in new images.
Public/Granted literature
- US20210374970A1 METHOD TO GENERATE NEURAL NETWORK TRAINING IMAGE ANNOTATIONS Public/Granted day:2021-12-02
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