Abstract

For an artifact such as a robot or a virtual agent to respond appropriately to human social touch behavior, it should be able to automatically detect and recognize touch. This paper describes the data collection of CoST: Corpus of Social Touch, a data set containing 7805 captures of 14 different social touch gestures. All touch gestures were performed in three variants: gentle, normal and rough on a pressure sensor grid wrapped around a mannequin arm. Recognition of these 14 gesture classes using various classifiers yielded accuracies up to 60 %; moreover, gentle gestures proved to be harder to classify than normal and rough gestures. We further investigated how different classifiers, interpersonal differences, gesture confusions and gesture variants affected the recognition accuracy. Finally, we present directions for further research to ensure proper transfer of the touch modality from interpersonal interaction to areas such as human–robot interaction (HRI).

Highlights

  • Touch gestures can be used in social interaction to communicate and express different emotions [14]

  • We focus on the recognition of a list of relevant social touch gestures

  • Classification of 14 gesture classes independent of variants resulted in an overall accuracy of up to 60 % using Support Vector Machine (SVM) with the Radial Basis Function (RBF) kernel, which is more than 8 times higher than classification by random guessing (≈7 %)

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Summary

Introduction

Touch gestures can be used in social interaction to communicate and express different emotions [14]. The sense of touch can be used to explore our environment and manipulate objects such as tools, which can be highly functional [13]. As opposed to functional touch, Haans and IJsselsteijn [13] described social touch as all instances of interpersonal touch, whether this is accidental (e.g. bumping into someone on the street) or conscious (e.g. comforting someone who is upset). We broaden this definition to include social touch interaction between humans and artifacts such as robots and virtual agents. The addition of tactile interaction can benefit robot therapy in which robots are used to comfort people in stressful environments, for instance, children in hospitals [19] and elderly people in nursing homes [37]

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