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
HiNet: Hybrid Inherited Feature Learning Network for Facial Expression Recognition
TL;DR: The experimental and computational complexity analysis demonstrate the significant performance improvement of the proposed method over the state-of-the-art techniques in terms of recognition rate.
Proceedings ArticleDOI
A Novel Apex-Time Network for Cross-Dataset Micro-Expression Recognition
TL;DR: Zhang et al. as mentioned in this paper proposed a novel Apex-Time Network (ATNet) to recognize micro-expression based on spatial information from the apex frame as well as on temporal information from respective adjacent frames.
Proceedings ArticleDOI
Exemplar Hidden Markov Models for classification of facial expressions in videos
TL;DR: This paper proposes that dynamical models such as HMMs are advantageous for the facial expression problem space, when employed in a discriminative, exemplar-based classification framework, and yields state-of-the-art results on both posed and spontaneous expression datasets.
Journal ArticleDOI
Discriminative multi-layer illumination-robust feature extraction for face recognition
TL;DR: A discriminative multi-layer illumination-robust feature extraction (DMI) model is proposed to address the problem of tackling illumination variation and shows that DMI performs better than the related methods, especially in difficult lighting conditions.
Proceedings ArticleDOI
Former-DFER: Dynamic Facial Expression Recognition Transformer
Zengqun Zhao,Qingshan Liu +1 more
TL;DR: Wang et al. as mentioned in this paper proposed a dynamic facial expression recognition transformer (former-DFER) for the in-the-wild scenario, which mainly consists of a convolutional spatial transformer (CS-former) and a temporal transformer (T-former).
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.