Human perceptual and affective responses change dynamically when stimuli are experienced. In this study, we developed a method for modeling the causal structures of affective dynamics using time-series data. Using the temporal dominance of sensations m…
Aspect-based sentiment analysis (ABSA) is crucial for exploring user feedbacks and preferences on produces or services. Although numerous classical deep learning-based methods have been proposed in previous literature, several useful cues (e.g., contex…
Measuring user engagement in interactive tasks can facilitate numerous applications toward optimizing user experience, ranging from eLearning to gaming. However, a significant challenge is the lack of non-contact engagement estimation methods that are …
The massive and growing burden imposed on modern society by depression has motivated investigations into early detection through automated, scalable and non-invasive methods, including those based on speech. However, speech-based methods that capture a…
Recently, emotion recognition in real sceneries such as in the wild has attracted extensive attention in affective computing, because existing spontaneous emotions in real sceneries are more challenging and difficult to identify than other emotions. Mo…
In a joint action, a group of individuals coordinate their movements to reach a shared goal. When a change–i.e., an event that affects group functioning–occurs, the group adopts strategies to face it. This article investigates how a chang…
Facial Attribute Classification (FAC) has attracted increasing attention in computer vision and pattern recognition. However, state-of-the-art FAC methods perform face detection/alignment and FAC independently. The inherent dependencies between these t…
Appraisal theories are a prominent approach for the explanation and prediction of emotions. According to these theories, the subjective perception of an emotion results from a series of specific event evaluations. To validate and extend one of the most…
The aim of this study is to recognize human emotions from electroencephalographic (EEG) signals using deep neural networks. Large training data is an important prerequisite for successful implementation of deep neural networks. In this view, we propose…
Facial expression recognition (FER) is crucial for social communication. However, current studies present limitations when addressing facial expression difference due to demographic variation, such as race, gender, and age, etc. In this article, we fir…