Affective Computing

Abstract

According to Rosalind Picard, if we want computers to be genuinely intelligent and to interact naturally with us, we must give computers the ability to recognize, understand, even to have and express emotions. The latest scientific findings indicate that emotions play an essential role in decision making, perception, learning, and more—that is, they influence the very mechanisms of rational thinking. Not only too much, but too little emotion can impair decision making. According to Rosalind Picard, if we want computers to be genuinely intelligent and to interact naturally with us, we must give computers the ability to recognize, understand, even to have and express emotions. Part 1 of this book provides the intellectual framework for affective computing. It includes background on human emotions, requirements for emotionally intelligent computers, applications of affective computing, and moral and social questions raised by the technology. Part 2 discusses the design and construction of affective computers. Although this material is more technical than that in Part 1, the author has kept it less technical than typical scientific publications in order to make it accessible to newcomers. Topics in Part 2 include signal-based representations of emotions, human affect recognition as a pattern recognition and learning problem, recent and ongoing efforts to build models of emotion for synthesizing emotions in computers, and the new application area of affective wearable computers.

The urban brain: analysing outdoor physical activity with mobile EEG

“…Brain studies are increasingly relevant as the development of affective computing7 and brain–computer interfaces (BCI) enable researchers and designers to measure brain activity in environmental settings 8. Although functional brain imaging has been used for subjects viewing environmental scenes in a laboratory setting,9 no field data are available to our knowledge.…”

Natural and Artificial Cognition: On the Proper Place of Reason

“…Once again, there is tremendous potential for a psychologically realistic foundation to play a role. Ever-increasing attention is paid in robotics to recognising, simulating, and even incorporating emotions (or emotion-analogs, if the reader prefers) (Picard 1998). But existing attempts lack the unification of emotions, drives, and motivations that can be achieved when a primordial body map is used as the basis for notions of affect, somatic markers, and momentary thought-action repertoires.…”

Action-perception cycle learning for incremental emotion recognition in a movie clip using 3D fuzzy GIST based on visual and EEG signals

“…The horizontal lines in each movie frame rep- resent calmness, stability and openness, whereas the vertical line represents directness and definitude. The circle and soft edge in the movie frame induce grace and rhythm [32]. Besides, it is well known that color information contained in the successive images dramatically affects human emotional states [39].…”

“…Human emotion is induced by stimulating factors of successive images such as a movie clip [32]. Accordingly [38], there exists a relationship between the line directions and the dynamic sensation of the successive images.…”

“…Despite major advances in this area, recognizing, understanding, and responding to human emotions still remain as challenges for autonomous intelligent systems. Empirical research on emotion is characterized by a wide variety of methodologies [32]. Given the understanding of human emotion, it is possible to assume that lowlevel emotions are automatically generated and they are primarily triggered by perceptual features of environment.…”