Face alignment by Explicit Shape Regression

2012 ◽  
Author(s):  
Xudong Cao ◽  
Yichen Wei ◽  
Fang Wen ◽  
Jian Sun
Keyword(s):  
Face Alignment ◽  
Shape Regression

scholarly journals Multi-feature shape regression for face alignment

2018 ◽  
Vol 2018 (1) ◽  
Author(s):  
Wei-Jong Yang ◽  
Yi-Chen Chen ◽  
Pau-Choo Chung ◽  
Jar-Ferr Yang
Keyword(s):  
Face Alignment ◽  
Shape Regression

Direct Shape Regression Networks for End-to-End Face Alignment

2018 ◽  
Author(s):  
Xin Miao ◽  
Xiantong Zhen ◽  
Xianglong Liu ◽  
Cheng Deng ◽  
Vassilis Athitsos ◽  
...  
Keyword(s):  
Face Alignment ◽  
Shape Regression ◽  
End To End

Improved explicit shape regression face alignment algorithm

2018 ◽  
Author(s):  
Lin Cong ◽  
Zhang Ting ◽  
Lv Chongshan ◽  
Wu Wei ◽  
Zhan Xiang ◽  
...  
Keyword(s):  
Face Alignment ◽  
Alignment Algorithm ◽  
Shape Regression

Face Alignment by Explicit Shape Regression

2013 ◽  
Vol 107 (2) ◽  
pp. 177-190 ◽  
Author(s):  
Xudong Cao ◽  
Yichen Wei ◽  
Fang Wen ◽  
Jian Sun
Keyword(s):  
Face Alignment ◽  
Shape Regression

scholarly journals Face Alignment in Thermal Infrared Images Using Cascaded Shape Regression

2021 ◽  
Vol 18 (4) ◽  
pp. 1776
Author(s):  
Kent Nagumo ◽  
Tomohiro Kobayashi ◽  
Kosuke Oiwa ◽  
Akio Nozawa
Keyword(s):  
Skin Temperature ◽  
Real Time ◽  
Region Of Interest ◽  
Thermal Infrared ◽  
Appearance Model ◽  
Face Alignment ◽  
Infrared Images ◽  
Time Performance ◽  
Thermal Infrared Images ◽  
Shape Regression

The evaluation of physiological and psychological states using thermal infrared images is based on the skin temperature of specific regions of interest, such as the nose, mouth, and cheeks. To extract the skin temperature of the region of interest, face alignment in thermal infrared images is necessary. To date, the Active Appearance Model (AAM) has been used for face alignment in thermal infrared images. However, computation using this method is costly, and it has a low real-time performance. Conversely, face alignment of visible images using Cascaded Shape Regression (CSR) has been reported to have high real-time performance. However, no studies have been reported on face alignment in thermal infrared images using CSR. Therefore, the objective of this study was to verify the speed and robustness of face alignment in thermal infrared images using CSR. The results suggest that face alignment using CSR is more robust and computationally faster than AAM.

Non-linear Boosting Regression for Multi-view Face Alignment

2010 ◽  
Vol 36 (4) ◽  
pp. 522-527
Author(s):  
Yan-Chao SU ◽  
Hai-Zhou AI ◽  
Shi-Hong LAO
Keyword(s):  
Face Alignment ◽  
Non Linear
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