Download Affective Computing and Intelligent Interaction: 4th by Arvid Kappas (auth.), Sidney D’Mello, Arthur Graesser, Björn PDF

By Arvid Kappas (auth.), Sidney D’Mello, Arthur Graesser, Björn Schuller, Jean-Claude Martin (eds.)

The two-volume set LNCS 6974 and LNCS 6975 constitutes the refereed lawsuits of the Fourth overseas convention on Affective Computing and clever interplay, ACII 2011, held in Memphis,TN, united states, in October 2011.
The a hundred thirty five papers during this quantity set offered including three invited talks have been conscientiously reviewed and chosen from 196 submissions. The papers are geared up in topical sections on acceptance and synthesis of human impact, affect-sensitive functions, methodological concerns in affective computing, affective and social robotics, affective and behavioral interfaces, suitable insights from psychology, affective databases, evaluate and annotation tools.

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Additional info for Affective Computing and Intelligent Interaction: 4th International Conference, ACII 2011, Memphis, TN, USA, October 9–12, 2011, Proceedings, Part I

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2 Procedure The study consisted of recording the physiological signals while subjects viewed the selected set of emotionally charged IAPS images for approximately 60 minutes over 5 sessions. Trials consisted of presenting each image for 12 seconds, followed by a self report questionnaire, where subjects had to select one of the four categories mentioned above. A blank screen was presented for 8 seconds to allow physiological activity to return to baseline levels before every new image appeared.

D´Mello et al. ): ACII 2011, Part I, LNCS 6974, pp. 4–13, 2011. © Springer-Verlag Berlin Heidelberg 2011 Affective Modeling from Multichannel Physiology: Analysis of Day Differences 5 approach, which combines decisions from multiple classifiers. This approach was validated on physiological affective data collected from multiple subjects over multiple sessions that spanned several days. 1 Day Differences and Non-stationarity of Affective Physiological Data Picard and colleagues [6] convincingly demonstrated that affective physiological data recorded from one subject across multiple days exhibited considerable day to day variations.

For example, the NegativeValence label of day one would be labeled D1_ _NV. The purpose is to assess how valence and arouusal cluster in a physiological space s on different days. Overall there were 16 datasetss (4 subjects x 2 labeling valencce/arousal). Top five features were separately selected frrom each dataset using chi sq quare feature selection. Figure 1 presents a dendrogrram obtained from hierarchical clustering on the data for one subject. The clusters w were computed using the singlee linkage method [22] based on distances (Mahalanobbis) between group means.

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