Journal ArticleDOI
Facial expression recognition from near-infrared videos
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TLDR
A novel research on a dynamic facial expression recognition, using near-infrared (NIR) video sequences and LBP-TOP feature descriptors and component-based facial features are presented to combine geometric and appearance information, providing an effective way for representing the facial expressions.About:
This article is published in Image and Vision Computing.The article was published on 2011-08-01. It has received 586 citations till now. The article focuses on the topics: Three-dimensional face recognition & Face hallucination.read more
Citations
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Journal ArticleDOI
Three-Stream Convolutional Neural Network with Squeeze-and-Excitation Block for Near-Infrared Facial Expression Recognition
TL;DR: A three-stream three-dimensional convolution neural network with a squeeze-and-excitation (SE) block for NIR facial expression recognition that has a higher recognition rate than some state-of-the-art algorithms.
Journal ArticleDOI
Deep cross feature adaptive network for facial emotion classification
TL;DR: A novel CNN-based model named as Deep Cross Feature Adaptive Network (DCFA-CNN) for facial expression recognition that embedded a two-branch cross-relationship to collect information of ShFeat and TexFeat block to boost discriminability of the network.
Proceedings ArticleDOI
FERV39k: A Large-Scale Multi-Scene Dataset for Facial Expression Recognition in Videos
Yan Chun Wang,Yixuan Sun,Yiwen Huang,Zhongying Liu,Shu Jing Gao,Wei Zhang,Weifeng Ge,Wenqiang Zhang +7 more
TL;DR: A large-scale multi-scene dataset for facial expression recognition (FER) in videos, coined as FERV39k is built and key components of DFER by ablation studies are systematically investigated.
Posted Content
Generative Adversarial Networks in Human Emotion Synthesis:A Review
TL;DR: A comprehensive survey of recent advances in human emotion synthesis by studying available databases, advantages, and disadvantages of the generative models along with the related training strategies considering two principal human communication modalities, namely audio and video.
Journal ArticleDOI
Geometrical Features and Active Appearance Model Applied to Facial Expression Recognition
TL;DR: A geometrical descriptor based on the calculation of distances from coordinates of facial fiducial points, which are used as features for training support vector machines (SVM) to classify emotions demonstrated to be very competitive, achieving high classification F-score rates.
References
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Multiresolution gray-scale and rotation invariant texture classification with local binary patterns
TL;DR: A generalized gray-scale and rotation invariant operator presentation that allows for detecting the "uniform" patterns for any quantization of the angular space and for any spatial resolution and presents a method for combining multiple operators for multiresolution analysis.
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Robust Face Recognition via Sparse Representation
TL;DR: This work considers the problem of automatically recognizing human faces from frontal views with varying expression and illumination, as well as occlusion and disguise, and proposes a general classification algorithm for (image-based) object recognition based on a sparse representation computed by C1-minimization.
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On combining classifiers
TL;DR: A common theoretical framework for combining classifiers which use distinct pattern representations is developed and it is shown that many existing schemes can be considered as special cases of compound classification where all the pattern representations are used jointly to make a decision.
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From few to many: illumination cone models for face recognition under variable lighting and pose
TL;DR: A generative appearance-based method for recognizing human faces under variation in lighting and viewpoint that exploits the fact that the set of images of an object in fixed pose but under all possible illumination conditions, is a convex cone in the space of images.