Robust facial landmark detection and tracking across poses and expressions for in-the-wild monocular video
Abstract We present a novel approach for automatically detecting and tracking facial landmarks across poses and expressions from in-the-wild monocular video data, e.g., YouTube videos and smartphone recordings. Our method does not require any calibration or manual adjustment for new individual input...
Main Authors: | , , , , |
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Format: | Article |
Language: | English |
Published: |
SpringerOpen
2017-03-01
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Series: | Computational Visual Media |
Subjects: | |
Online Access: | http://link.springer.com/article/10.1007/s41095-016-0068-y |