Facial emotion recognition (FER) is a computer vision process aimed at detecting and
classifying human emotional expressions. FER systems are currently used in a vast range of …

The automatic detection of eye positions, their temporal consistency, and their map** into
a line of sight in the real world (to find where a person is looking at) is reported in the …

Images can convey rich semantics and induce various emotions in viewers. Recently, with
the rapid advancement of emotional intelligence and the explosive growth of visual data …

Human emotion is expressed, perceived and captured using a variety of dynamic data
modalities, such as speech (verbal), videos (facial expressions) and motion sensors (body …

The prevailing use of both images and text to express opinions on the web leads to the need
for multimodal sentiment recognition. Some commonly used social media data containing …

Affective computing is a nascent field situated at the intersection of artificial intelligence with
social and behavioral science. It studies how human emotions are perceived and …

Attention is a human's concentration of awareness on a specific moment or information. The
level of attention describes how deep the focus is on that specific moment or information …

Attending selectively to emotion-eliciting stimuli is intrinsic to human vision. In this research,
we investigate how emotion-elicitation features of images relate to human selective …

Saliency prediction refers to the computational task of modeling overt attention. Social cues
greatly influence our attention, consequently altering our eye movements and behavior. To …

It is not an easy task for organizers to observe the engagement level of a video meeting
audience. This research was conducted to build an intelligent system to enhance the …