Journal ArticleDOI
Facial expression recognition from near-infrared videos
Reads0
Chats0
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
More filters
Journal ArticleDOI
Detection of Genuine and Posed Facial Expressions of Emotion: Databases and Methods.
TL;DR: In this paper, a general review of the relevant research, including several spontaneous vs. posed facial expression databases and various computer vision based detection methods is presented along with open issues and technical challenges in this nascent field.
Posted Content
From Facial Expression Recognition to Interpersonal Relation Prediction
TL;DR: In this paper, a multi-task Siamese network is proposed to predict inter-personal relations. But the model is limited to face images and does not handle other attributes, such as gender, age, and head pose.
Journal ArticleDOI
Leveraging 3D blendshape for facial expression recognition using CNN
TL;DR: In order to train the blendshape network, a large blendshape image dataset is constructed, namely BlendshapeExp, which gets 297,490 images with ground truth blendshape coefficients and is trained to regress these coefficients from a single image.
Book ChapterDOI
Deep Learning-Based Emotion Recognition from Real-Time Videos
TL;DR: A novel framework for emotional state detection from facial expression targeted to learning environments based on a convolutional deep neural network that classifies people’s emotions that are captured through a web-cam and integrated into an affective pedagogical agent system.
Posted Content
Discriminatively Trained Latent Ordinal Model for Video Classification
Karan Sikka,Gaurav Sharma +1 more
TL;DR: In this paper, a weakly supervised learning method was proposed to model the video as a sequence of automatically mined, discriminative sub-events (e.g., onset and offset phase for "smile", running and jumping for "highjump").
References
More filters
Journal ArticleDOI
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.
Journal ArticleDOI
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.
Journal ArticleDOI
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.
Journal ArticleDOI
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.