Invention Application
- Patent Title: UTILIZING DEEP LEARNING FOR AUTOMATIC DIGITAL IMAGE SEGMENTATION AND STYLIZATION
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Application No.: US15679989Application Date: 2017-08-17
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Publication No.: US20170344860A1Publication Date: 2017-11-30
- Inventor: Ian Sachs , Xiaoyong Shen , Sylvain Paris , Aaron Hertzmann , Elya Shechtman , Brian Price
- Applicant: Adobe Systems Incorporated
- Main IPC: G06K9/66
- IPC: G06K9/66 ; G06K9/46 ; G06T7/90

Abstract:
Systems and methods are disclosed for segregating target individuals represented in a probe digital image from background pixels in the probe digital image. In particular, in one or more embodiments, the disclosed systems and methods train a neural network based on two or more of training position channels, training shape input channels, training color channels, or training object data. Moreover, in one or more embodiments, the disclosed systems and methods utilize the trained neural network to select a target individual in a probe digital image. Specifically, in one or more embodiments, the disclosed systems and methods generate position channels, training shape input channels, and color channels corresponding the probe digital image, and utilize the generated channels in conjunction with the trained neural network to select the target individual.
Public/Granted literature
- US09978003B2 Utilizing deep learning for automatic digital image segmentation and stylization Public/Granted day:2018-05-22
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