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...
Saved in:
Main Authors: | Sheng, Lu, Cai, Jianfei, Cham, Tat-Jen, Pavlovic, Vladimir, Ngan, King Ngi |
---|---|
Other Authors: | School of Computer Science and Engineering |
Format: | Conference or Workshop Item |
Language: | English |
Published: |
2020
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/138494 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Visibility constrained generative model for depth-based 3D facial pose tracking
by: Sheng, Lu, et al.
Published: (2020) -
FACIAL LANDMARK DETECTION TOWARDS ROBUSTNESS
by: XIAO SHENGTAO
Published: (2017) -
GeoConv: geodesic guided convolution for facial action unit recognition
by: Chen, Yuedong, et al.
Published: (2023) -
Handling pose variation in face recognition using SIFT
by: Bhattacharya, B., et al.
Published: (2014) -
Analyzing facial expressions and hand gestures in Filipino students' programming sessions
by: Tiam-Lee, Thomas James Z., et al.
Published: (2017)