Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns
IEEE Transactions on Pattern Analysis and Machine Intelligence
Comprehensive Database for Facial Expression Analysis
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Active and Dynamic Information Fusion for Facial Expression Understanding from Image Sequences
IEEE Transactions on Pattern Analysis and Machine Intelligence
Feature-Based Detection of Facial Landmarks from Neutral and Expressive Facial Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
SVM-KNN: Discriminative Nearest Neighbor Classification for Visual Category Recognition
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Dynamic Texture Recognition Using Local Binary Patterns with an Application to Facial Expressions
IEEE Transactions on Pattern Analysis and Machine Intelligence
An analysis of facial expression recognition under partial facial image occlusion
Image and Vision Computing
Reconstruction and Recognition of Occluded Facial Expressions Using PCA
ACII '07 Proceedings of the 2nd international conference on Affective Computing and Intelligent Interaction
A Survey of Affect Recognition Methods: Audio, Visual, and Spontaneous Expressions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust Face Recognition via Sparse Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Facial-component-based bag of words and PHOG descriptor for facial expression recognition
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Occluded facial expression tracking
SCIA'07 Proceedings of the 15th Scandinavian conference on Image analysis
Combining dynamic texture and structural features for speaker identification
Proceedings of the 2nd ACM workshop on Multimedia in forensics, security and intelligence
LIBSVM: A library for support vector machines
ACM Transactions on Intelligent Systems and Technology (TIST)
Expression recognition in videos using a weighted component-based feature descriptor
SCIA'11 Proceedings of the 17th Scandinavian conference on Image analysis
ICME '11 Proceedings of the 2011 IEEE International Conference on Multimedia and Expo
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Hough forest-based facial expression recognition from video sequences
ECCV'10 Proceedings of the 11th European conference on Trends and Topics in Computer Vision - Volume Part I
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Facial occlusion is a challenging research topic in facial expression recognition (FER). This has resulted in the need to develop some interesting facial representations and occlusion detection methods in order to extend the FER to uncontrolled environments. It should be noted that most of the previous work focuses on these two issues separately, and on static images. We are thus motivated to propose a complete system consisting of facial representations, occlusion detection, and multiple feature fusion in video sequences. For achieving a robust facial representation, we propose an approach deriving six feature vectors from eyes, nose and mouth components to form a facial representation. These features with temporal cues are generated by the dynamic texture and structural shape feature descriptors. On the other hand, occlusion detection is still mainly realized by the traditional classifiers or model comparison. Recently, sparse representation has been proposed as an efficient method against occlusion, while it is correlated with facial identity in FER, unless using an appropriate facial representation. Thus, we present an evaluation demonstrating that the proposed facial representation is independent of facial identity. Inspired by Mercier et al. (2007), we then exploit the use of the sparse representation and residual statistics to occlusion detection of the image sequences. As concatenating six feature vectors into one causes the curse of dimensionality, we propose multiple feature fusion consisting of fusion module and weight learning. Experimental results on the Extended Cohn-Kanade database and its simulated database demonstrate that our framework outperforms the state-of-the-art methods for FER in normal videos, and especially, in partial occlusion videos.