In this paper we introduce a novel method of estimating romantic, social and sexual attraction between two people by quantifying their bodily coordination using wearable sensors in a speed-date setting. We developed simple synchrony and convergence features, inspired from the literature and specifically adapted to be extracted from accelerometer data. To our knowledge, this is the first time that motion convergence is used for estimating attraction. Our features could predict one-way social attraction with a 73% Area under the ROC curve (AUC), out-performing previous work in a similar setting. We also showed that prediction performance increased when the male and female data are separated. We could also predict mutual romantic attraction with an AUC of 80%. Finally, we found that social attraction could be predicted better from movement correlation features whereas for romantic and sexual interest mimicry features were better indicators. Additionally, we found that 'mimicking of female to male' and 'convergence of female's movement to male's' were indicators of sexual and romantic mutual attraction in our data.

Original languageEnglish
Title of host publication2019 8th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos, ACIIW 2019
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages154-160
Number of pages7
ISBN (Electronic)9781728138916
DOIs
Publication statusPublished - 1 Sep 2019
Event8th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos, ACIIW 2019 - Cambridge, United Kingdom
Duration: 3 Sep 20196 Sep 2019

Conference

Conference8th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos, ACIIW 2019
CountryUnited Kingdom
CityCambridge
Period3/09/196/09/19

    Research areas

  • Attraction, convergence, dyadic interactions, speed-dates, synchrony, wearable acceleration

ID: 68945181