Abstract
Touch behavior is of great importance during social interaction. To transfer the tactile modality from interpersonal interaction to other areas such as Human-Robot Interaction (HRI) and remote communication automatic recognition of social touch is necessary. This paper introduces CoST: Corpus of Social Touch, a collection containing 7805 instances of 14 different social touch gestures. The gestures were performed in three variations: gentle, normal and rough, on a sensor grid wrapped around a mannequin arm. Recognition of the rough variations of these 14 gesture classes using Bayesian classifiers and Support Vector Machines (SVMs) resulted in an overall accuracy of 54% and 53%, respectively. Furthermore, this paper provides more insight into the challenges of automatic recognition of social touch gestures, including which gestures can be recognized more easily and which are more difficult to recognize.
Original language | Undefined |
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Title of host publication | Proceedings of the 16th International Conference on Multimodal Interaction, ICMI 2014 |
Place of Publication | New York |
Publisher | Association for Computing Machinery |
Pages | 120-127 |
Number of pages | 8 |
ISBN (Print) | 978-1-4503-2885-2 |
DOIs | |
Publication status | Published - Nov 2014 |
Event | 16th International Conference on Multimodal Interaction, ICMI 2014 - Istanbul, Turkey, Istanbul, Turkey Duration: 12 Nov 2014 → 16 Nov 2014 Conference number: 16 |
Publication series
Name | |
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Publisher | ACM |
Conference
Conference | 16th International Conference on Multimodal Interaction, ICMI 2014 |
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Abbreviated title | ICMI |
Country/Territory | Turkey |
City | Istanbul |
Period | 12/11/14 → 16/11/14 |
Other | 12-16 November 2014 |
Keywords
- EWI-25280
- Touch gesture recognition
- METIS-309648
- Touch corpus
- IR-93288
- Social Touch
Datasets
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Corpus of Social Touch (CoST)
Jung, M. M. (Creator), University of Twente, 1 Jun 2016
DOI: 10.4121/uuid:5ef62345-3b3e-479c-8e1d-c922748c9b29
Dataset