Invention Grant
- Patent Title: Utilizing deep learning for automatic digital image segmentation and stylization
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Application No.: US15005855Application Date: 2016-01-25
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Publication No.: US09773196B2Publication Date: 2017-09-26
- Inventor: Ian Sachs , Xiaoyong Shen , Sylvain Paris , Aaron Hertzmann , Elya Shechtman , Brian Price
- Applicant: Adobe Systems Incorporated
- Applicant Address: US CA San Jose
- Assignee: ADOBE SYSTEMS INCORPORATED
- Current Assignee: ADOBE SYSTEMS INCORPORATED
- Current Assignee Address: US CA San Jose
- Agency: Keller Jolley Preece
- Main IPC: G06K9/62
- IPC: G06K9/62 ; G06K9/66 ; G06T7/00 ; G06K9/46

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
- US20170213112A1 UTILIZING DEEP LEARNING FOR AUTOMATIC DIGITAL IMAGE SEGMENTATION AND STYLIZATION Public/Granted day:2017-07-27
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