The global affective computing market is envisioned to create high growth prospects on the back of the rising deployment of machine and human interaction technologies. With enabling technologies already making a mark with their adoption in a range of industry verticals, it could be said that the market has started to evolve. Facial feature extraction software collecting a handsome demand in the recent years is expected to augur well for the growth of the deployment of cameras in affective computing systems. Detection of psychological disorders, facial expression recognition for dyslexia, autism, and other disorders in specially-abled children, and various other applications could increase the use of affective computing technology. Life sciences and healthcare are prognosticated to showcase a promising rise in the demand for affective computing.
This special track will serve as a forum to unite researchers from the interdisciplinary arena that encompasses computer science, engineering, HCI, psychology, and education to exchange ideas, frameworks, methods, and tools relating to affective computing. Although the last decade has been ripe with theory and applications relevant to AC, these advances are accompanied by a new set of challenges. By providing a framework to discuss and evaluate novel research, we hope to leverage recent advances to speed-up future research in this area.
Our research has contributed to: (1) Designing new ways for people to communicate affective-cognitive states, especially through creation of novel wearable sensors and new machine learning algorithms that jointly analyze multimodal channels of information; (2) Creating new techniques to assess frustration, stress, and mood indirectly, through natural interaction and conversation; (3) Showing how computers can be more emotionally intelligent, especially responding to a person's frustration in a way that reduces negative feelings; (4) Inventing personal technologies for improving self-awareness of affective state and its selective communication to others; (5) Increasing understanding of how affect influences personal health; and (6) Pioneering studies examining ethical issues in affective computing.