A generative model for depth-based robust 3D facial pose tracking

A generative model for depth-based robust 3D facial pose tracking

We consider the problem of depth-based robust 3D facial pose tracking under unconstrained scenarios with heavy occlusions and arbitrary facial expression variations. Unlike the previous depth-based discriminative or data-driven methods that require sophisticated training or manual intervention, we p...

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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: Conference Paper
Language:English
Published: 2020
Subjects:
Engineering::Computer science and engineering
Computer Vision
Face Recognition
Online Access:https://hdl.handle.net/10356/138494

Internet

https://hdl.handle.net/10356/138494

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