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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Bibliographic Details
Main Authors: Sheng, Lu, Cai, Jianfei, Cham, Tat-Jen, Pavlovic, Vladimir, Ngan, King Ngi
Other Authors: School of Computer Science and Engineering
Format: Article
Language:English
Published: 2020
Subjects:
Online Access:https://hdl.handle.net/10356/138265
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Institution: Nanyang Technological University
Language: English