1st International Workshop on Multimodal Pattern Recognition of Social Signals in Human Computer Interaction (MPRSS) -- NOV 11, 2012 -- Tsukuba, JAPAN ; Altun, Kerem/0000-0002-5493-8921 ; WOS:000362271100005 ; A pet cat or dog's ability to respond to our emotional state opens an interaction channel with high visceral impact, which social robots may also be able to access. Touch is a key but understudied element; here, we explore its emotional content in the context of a furry robot pet. We asked participants to imagine feeling nine emotions located in a 2-D arousal-valence affect space, then to express them by touching a lap-sized robot prototype equipped with pressure sensors and accelerometer. We found overall correct classification (Random Forests) within the 2-D grid of 36% (all participants combined) and 48% (average of participants classified individually); chance 11%. Rates rose to 56% in the high arousal zone. To better understand classifier performance, we defined and analyzed new metrics that better indicate closeness of the gestural expressions. We also present a method to combine direct affect recognition with affect inferred from gesture recognition. This analysis provides a unique first insight into the nature and quality of affective touch, with implications as a design tool and for incorporating unintrusive affect sensing into deployed interactions. (C) 2014 Elsevier B.V. All rights reserved. ; Int Assoc Pattern Recognit (IAPR), TC3 ; NSERCNatural Sciences and Engineering Research Council of Canada (NSERC) ; We thank our experiment participants, and Dr. M. Sedlmair for visualization advice. This work was supported by NSERC.


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    Title :

    Recognizing affect in human touch of a robot


    Contributors:

    Publication date :

    2015-01-01



    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    629



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