Invention Grant
- Patent Title: Facial expression recognition utilizing unsupervised learning
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Application No.: US15856271Application Date: 2017-12-28
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Publication No.: US10789456B2Publication Date: 2020-09-29
- Inventor: Yu Luo , Xin Lu , Jen-Chan Jeff Chien
- Applicant: Adobe Inc.
- Applicant Address: US CA San Jose
- Assignee: Adobe Inc.
- Current Assignee: Adobe Inc.
- Current Assignee Address: US CA San Jose
- Agency: Finch & Maloney PLLC
- Main IPC: G06K9/00
- IPC: G06K9/00 ; G06N3/08 ; G06K9/66 ; G06N3/04 ; G06N5/00 ; G06N20/20 ; G06N20/10

Abstract:
Techniques are disclosed for a facial expression classification. In an embodiment, a multi-class classifier is trained using labelled training images, each training image including a facial expression. The trained classifier is then used to predict expressions for unlabelled video frames, whereby each frame is effectively labelled with a predicted expression. In addition, each predicted expression can be associated with a confidence score. Anchor frames can then be identified in the labelled video frames, based on the confidence scores of those frames (anchor frames are frames having a confidence score above an established threshold). Then, for each labelled video frame between two anchor frames, the predicted expression is refined or otherwise updated using interpolation, thereby providing a set of video frames having calibrated expression labels. These calibrated labelled video frames can then be used to further train the previously trained facial expression classifier, thereby providing a supplementally trained facial expression classifier.
Public/Granted literature
- US20190205625A1 FACIAL EXPRESSION RECOGNITION UTILIZING UNSUPERVISED LEARNING Public/Granted day:2019-07-04
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