Visibility constrained generative model for depth-based 3D facial pose tracking
In this paper, we propose a generative framework that unifies depth-based 3D facial pose tracking and face model adaptation on-the-fly, in the unconstrained scenarios with heavy occlusions and arbitrary facial expression variations. Specifically, we introduce a statistical 3D morphable model that fl...
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Main Authors: | Sheng, Lu, Cai, Jianfei, Cham, Tat-Jen, Pavlovic, Vladimir, Ngan, King Ngi |
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Other Authors: | School of Computer Science and Engineering |
Format: | Article |
Language: | English |
Published: |
2020
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/138265 |
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Institution: | Nanyang Technological University |
Language: | English |
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