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

• المؤلفون الرئيسيون: Sheng, Lu, Cai, Jianfei, Cham, Tat-Jen, Pavlovic, Vladimir, Ngan, King Ngi
• مؤلفون آخرون: School of Computer Science and Engineering
• التنسيق: مقال
• اللغة: English
• منشور في: 2020
• الموضوعات: Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision; 3D Facial Pose Tracking; Generative Model
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/138265
• المؤسسة: Nanyang Technological University

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...