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
Design of a CMOS image sensor pixel with embedded polysilicon nano-grating for near-infrared imaging enhancement.
Elie Cobo,S. Massenot,Alexandre Le Roch,Franck Corbière,Vincent Goiffon,Pierre Magnan,Jean-Luc Pelouard +6 more
TL;DR: In this article , a polysilicon nano-grating inside a pixel, at the transistor gate level of a 90 nm standard CMOS process, was evaluated through opto-electrical simulations.
Proceedings ArticleDOI
Excerpt of PPGface: Like What You Are Watching? Earphones Can “Feel” Your Facial Expressions
TL;DR: PPGface is proposed, a ubiquitous, easy-to-use, user-friendly facial expression recognition platform that leverages earable devices with built-in PPG sensor that can detect and recognize the user’s seven universal facial expressions and relevant body posture unobtrusively.
Journal ArticleDOI
When Facial Expression Recognition Meets Few-Shot Learning: A Joint and Alternate Learning Framework
TL;DR: This paper proposes a novel Emotion Guided Similarity Network (EGS-Net), consisting of an emotion branch and a similarity branch, based on a two-stage learning framework, which aims to identify unseen compound expressions with the model trained on easily accessible basic expression datasets.
Proceedings ArticleDOI
Recognition of Faces and Facial Attributes Using Accumulative Local Sparse Representations
Domingo Mery,Sandipan Banerjee +1 more
TL;DR: Experiments on three popular face databases show that ALSR outperforms representative methods in the literature, when a huge number of training images is not available.
Journal ArticleDOI
Self-Difference Convolutional Neural Network for Facial Expression Recognition
TL;DR: Li et al. as discussed by the authors proposed a self-difference convolutional network (SD-CNN) to address the intra-class variation issue in facial expression recognition, which achieved state-of-the-art performance with accuracies of 997% on CK+ and 913% on Oulu-CASIA.
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.