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...
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| Główni autorzy: | , , , , |
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| Format: | Artigo |
| Język: | Inglês |
| Wydane: |
Tsinghua University Press
2017-03-01
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| Seria: | Computational Visual Media |
| Hasła przedmiotowe: | |
| Dostęp online: | http://link.springer.com/article/10.1007/s41095-016-0068-y |
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