Visibility constrained generative model for depth-based 3D facial pose tracking

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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書目詳細資料
Main Authors:	Sheng, Lu, Cai, Jianfei, Cham, Tat-Jen, Pavlovic, Vladimir, Ngan, King Ngi
其他作者:	School of Computer Science and Engineering
格式:	Article
語言:	English
出版:	2020
主題:	Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision 3D Facial Pose Tracking Generative Model
在線閱讀:	https://hdl.handle.net/10356/138265
標簽:	添加標簽沒有標簽, 成為第一個標記此記錄!

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