Affective computing

Picard, Rosalind W.

doi:10.1037/e526112012-054

Cited by 2,199 publications

(1,920 citation statements)

References 0 publications

Supporting

Mentioning

1,702

Contrasting

Unclassified

111

Order By: Relevance

“…The importance of multimodality is the object of a large consensus among researchers studying communication in ethology (Partan and Marler 2005;Rowe 1999), emotion psychology (Ekman and Friesen 1967;Massaro and Egan 1996;Scherer and Ellgring 2007b), cognitive neuroscience (Ghazanfar and Schroeder 2006;Pourtois et al 2005), human-computer interaction (Jaimes and Sebe 2007), and affective computing (Bianchi-Berthouze and Lisetti 2002;Picard 1997). No one seems to question the idea that organisms communicate via a number of modalities: auditory, visual, olfactory, and tactile; and that modalities can include a number of channels, for example visual signals are displayed in the face, body, and hands.…”

Section: Multimodal Signalsmentioning

confidence: 99%

A psycho-ethological approach to social signal processing

Méhu

Scherer

2012

Cogn Process

View full text Add to dashboard Cite

The emerging field of social signal processing can benefit from a theoretical framework to guide future research activities. The present article aims at drawing attention to two areas of research that devoted considerable efforts to the understanding of social behaviour: ethology and social psychology. With a long tradition in the study of animal signals, ethology and evolutionary biology have developed theoretical concepts to account for the functional significance of signalling. For example, the consideration of divergent selective pressures responsible for the evolution of signalling and social cognition emphasized the importance of two classes of indicators: informative cues and communicative signals. Social psychology, on the other hand, investigates emotional expression and interpersonal relationships, with a focus on the mechanisms underlying the production and interpretation of social signals and cues. Based on the theoretical considerations developed in these two fields, we propose a model that integrates the processing of perceivable individual features (social signals and cues) with contextual information, and we suggest that output of computer-based processing systems should be derived in terms of functional significance rather than in terms of absolute conceptual meaning.

show abstract

Section: Multimodal Signalsmentioning

confidence: 99%

A psycho-ethological approach to social signal processing

Méhu

Scherer

2012

Cogn Process

View full text Add to dashboard Cite

show abstract

“…This is especially regrettable when other domains, e.g. Affective Computing (AC) [55] or Social Signal Processing (SSP) [66], pay significant attention to social, affective and emotional aspects of human behavior, but do not take into account scenarios relevant to surveillance and monitoring, especially when it comes to the analysis of large groups of people sharing the same physical space.…”

Section: Introductionmentioning

confidence: 99%

Socially intelligent surveillance and monitoring: Analysing social dimensions of physical space

Cristani

Murino

Vinciarelli

2010

2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops

View full text Add to dashboard Cite

In general terms, surveillance and monitoring technologies aim at understanding what people do in a given environment, whether this means to ensure the safety of workers on the factory floor, to detect crimes occurring in indoor or outdoor settings, or to monitor the flow of large crowds through public spaces. However, surveillance and monitoring technologies rarely consider that they analyze human behavior, a phenomenon subject to principles and laws rigorous enough to produce stable and predictable patterns corresponding to social, affective, and psychological phenomena. On the other hand, these phenomena are the subject of other computing domains, in particular Social Signal Processing and Affective Computing, that typically neglect scenarios relevant to surveillance and monitoring technologies, especially when it comes to social and affective dimensions of space in human activities. The goal of this paper is to show that the investigation of the overlapping area between surveillance and monitoring on one side, and Social Signal Processing and Affective Computing on the other side can bring significant progress in both domains and open a number of interesting research perspectives.

show abstract

“…Efforts to automate the Facial Actions Coding System started at the end of the 20th century [11] and have now become the focus of academic teams [29,3,53,10,48,26] and commercial ventures.…”

Section: Level Of Descriptionmentioning

confidence: 99%