Geometric Feature-Based Face Normalization for Facial Expression Recognition

2014 ◽  
Author(s):  
Dong-Ju Kim ◽  
Myoung-Kyu Sohn ◽  
Hyunduk Kim ◽  
Nuri Ryu
Keyword(s):  
Facial Expression ◽  
Facial Expression Recognition ◽  
Geometric Feature ◽  
Expression Recognition ◽  
Feature Based

scholarly journals An efficient multimodal 2D + 3D feature-based approach to automatic facial expression recognition

2015 ◽  
Vol 140 ◽  
pp. 83-92 ◽  
Author(s):  
Huibin Li ◽  
Huaxiong Ding ◽  
Di Huang ◽  
Yunhong Wang ◽  
Xi Zhao ◽  
...  
Keyword(s):  
Facial Expression ◽  
Facial Expression Recognition ◽  
Expression Recognition ◽  
Feature Based

Facial Expression Recognition Based on Monogenic Binary Coding

2014 ◽  
Vol 511-512 ◽  
pp. 437-440
Author(s):  
Xiao Xiao Xia ◽  
Zi Lu Ying ◽  
Wen Jin Chu
Keyword(s):  
Facial Expression ◽  
Facial Expression Recognition ◽  
Local Variation ◽  
Expression Recognition ◽  
Multi Scale ◽  
Linear Discrimination ◽  
Binary Coding ◽  
Japanese Female ◽  
Feature Based ◽  
Better Than

A new method based on Monogenic Binary Coding (MBC) is proposed for facial expression feature extraction and representation. Firstly, monogenic signal analysis is used to extract multi-scale magnitude, orientation and phase components. Secondly, Monogenic Binary Coding (MBC) is used to encode the monogenic local variation and intensity in local regions of each extracted component in each scale and local histograms are built. Then Blocked Fisher Linear Discrimination (BFLD) is used to reduce the dimensionality of histogram features and to enhance discrimination. Finally the three complementary components are fused for more effective facial expression recognition (FER). Experiment results on Japanese female expression database (JAFFE) show that the performance of the fusion method is even better than state-of-the-art local feature based FER methods such as Local Binary Pattern (LBP)+Sparse Representation (SRC), Local Phase Quantization (LPQ)+SRC ,etc.

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