scholarly journals A spatial-temporal framework based on histogram of gradients and optical flow for facial expression recognition in video sequences

2015 ◽  
Vol 48 (11) ◽  
pp. 3407-3416 ◽  
Author(s):  
Xijian Fan ◽  
Tardi Tjahjadi
Keyword(s):  
Facial Expression ◽  
Optical Flow ◽  
Facial Expression Recognition ◽  
Video Sequences ◽  
Expression Recognition ◽  
Histogram Of Gradients

Automatic Facial Expression Recognition by Facial Parts Location with Boosted-LBP

2013 ◽  
pp. 42-55
Author(s):  
Yi Ji ◽  
Khalid Idrissi
Keyword(s):  
Feature Extraction ◽  
Facial Expression ◽  
Facial Expressions ◽  
Facial Expression Recognition ◽  
Recognition System ◽  
Video Sequences ◽  
Polynomial Kernel ◽  
Expression Recognition ◽  
Emotional States ◽  
Small Set

This paper proposes an automatic facial expression recognition system, which uses new methods in both face detection and feature extraction. In this system, considering that facial expressions are related to a small set of muscles and limited ranges of motions, the facial expressions are recognized by these changes in video sequences. First, the differences between neutral and emotional states are detected. Faces can be automatically located from changing facial organs. Then, LBP features are applied and AdaBoost is used to find the most important features for each expression on essential facial parts. At last, SVM with polynomial kernel is used to classify expressions. The method is evaluated on JAFFE and MMI databases. The performances are better than other automatic or manual annotated systems.

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