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Facial Expression

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Using automated computer vision and machine learning to code facial expressions of affect and arousal: Implications for emotion dysregulation research.

Development and psychopathology
As early as infancy, caregivers' facial expressions shape children's behaviors, help them regulate their emotions, and encourage or dissuade their interpersonal agency. In childhood and adolescence, proficiencies in producing and decoding facial expr...

Using computer-vision and machine learning to automate facial coding of positive and negative affect intensity.

PloS one
Facial expressions are fundamental to interpersonal communication, including social interaction, and allow people of different ages, cultures, and languages to quickly and reliably convey emotional information. Historically, facial expression researc...

System for Face Recognition under Different Facial Expressions Using a New Associative Hybrid Model Amαβ-KNN for People with Visual Impairment or Prosopagnosia.

Sensors (Basel, Switzerland)
Face recognition is a natural skill that a child performs from the first days of life; unfortunately, there are people with visual or neurological problems that prevent the individual from performing the process visually. This work describes a system...

Group Differences in Facial Emotion Expression in Autism: Evidence for the Utility of Machine Classification.

Behavior therapy
Effective social communication relies, in part, on accurate nonverbal expression of emotion. To evaluate the nature of facial emotion expression (FEE) deficits in children with autism spectrum disorder (ASD), we compared 20 youths with ASD to a sampl...

The importance of recurrent top-down synaptic connections for the anticipation of dynamic emotions.

Neural networks : the official journal of the International Neural Network Society
Different studies have shown the efficiency of a feed-forward neural network in categorizing basic emotional facial expressions. However, recent findings in psychology and cognitive neuroscience suggest that visual recognition is not a pure bottom-up...

Early Expression Detection via Online Multi-Instance Learning With Nonlinear Extension.

IEEE transactions on neural networks and learning systems
Video-based facial expression recognition has received substantial attention over the past decade, while early expression detection (EED) is still a relatively new and challenging problem. The goal of EED is to identify an expression as quickly as po...

Unsupervised Domain Adaptation for Facial Expression Recognition Using Generative Adversarial Networks.

Computational intelligence and neuroscience
In the facial expression recognition task, a good-performing convolutional neural network (CNN) model trained on one dataset (source dataset) usually performs poorly on another dataset (target dataset). This is because the feature distribution of the...

Semantic measures: Using natural language processing to measure, differentiate, and describe psychological constructs.

Psychological methods
Psychological constructs, such as emotions, thoughts, and attitudes are often measured by asking individuals to reply to questions using closed-ended numerical rating scales. However, when asking people about their state of mind in a natural context ...

Wasserstein CNN: Learning Invariant Features for NIR-VIS Face Recognition.

IEEE transactions on pattern analysis and machine intelligence
Heterogeneous face recognition (HFR) aims at matching facial images acquired from different sensing modalities with mission-critical applications in forensics, security and commercial sectors. However, HFR presents more challenging issues than tradit...

Nonlinear analysis and synthesis of video images using deep dynamic bottleneck neural networks for face recognition.

Neural networks : the official journal of the International Neural Network Society
Nonlinear components extracted from deep structures of bottleneck neural networks exhibit a great ability to express input space in a low-dimensional manifold. Sharing and combining the components boost the capability of the neural networks to synthe...