Do they like me? Using video cues to predict desires during speed-dates

In this paper we introduce video features which are used to predict if people want to exchange contact information with the other in a speed-date, we also use these features to predict how physically attractive participants found their dates. Previous work on predicting and interpreting speed-dates has focused mainly on the audio channel. We use automatically extracted features related to position, proximity and motion. This paper shows that these features can be used to significantly outperform the baseline and have comparable performance to audio-only systems. The data used has been gathered from a real speed-date event, involving 16 participants. Experiments were carried out on 64 speed-dates lasting 5 minutes. The best performance on prediction exchanging contact information was 72% and 70% accuracy for males and females respectively, and 70% for both genders when predicting physical attraction.

[1]  Maja Pantic,et al.  Modeling hidden dynamics of multimodal cues for spontaneous agreement and disagreement recognition , 2011, Face and Gesture 2011.

[2]  J. Mccroskey,et al.  The measurement of interpersonal attraction , 1974 .

[3]  Elisa Ricci,et al.  Space speaks: towards socially and personality aware visual surveillance , 2010, MPVA '10.

[4]  Anton Nijholt,et al.  Measuring Multimodal Synchrony for Human-Computer Interaction , 2010, 2010 International Conference on Cyberworlds.

[5]  David Dryden Henningsen,et al.  Flirting with Meaning: An Examination of Miscommunication in Flirting Interactions , 2004 .

[6]  Daniel Jurafsky,et al.  It’s Not You, it’s Me: Detecting Flirting and its Misperception in Speed-Dates , 2009, EMNLP.

[7]  M. Patterson,et al.  Nonverbal Behavior and Social Psychology , 1982 .

[8]  T. Chartrand,et al.  The chameleon effect: the perception-behavior link and social interaction. , 1999, Journal of personality and social psychology.

[9]  Sandra Morris,et al.  PSYCHOLOGICAL CHARACTERISTICS AND INTERPERSONAL DISTANCE , 2001 .

[10]  E. Hall,et al.  The Hidden Dimension , 1970 .

[11]  Daniel Gatica-Perez,et al.  Automatic nonverbal analysis of social interaction in small groups: A review , 2009, Image Vis. Comput..

[12]  Maja Pantic,et al.  Social signal processing: Survey of an emerging domain , 2009, Image Vis. Comput..

[13]  Gerald Friedland,et al.  Estimating Dominance in Multi-Party Meetings Using Speaker Diarization , 2011, IEEE Transactions on Audio, Speech, and Language Processing.

[14]  A. Pentland,et al.  Thin slices of negotiation: predicting outcomes from conversational dynamics within the first 5 minutes. , 2007, The Journal of applied psychology.

[15]  Anmol Madan,et al.  Voices of Attraction , 2004 .

[16]  K. Grammer,et al.  Fuzziness of nonverbal courtship communication unblurred by motion energy detection. , 1999, Journal of personality and social psychology.

[17]  Alex Pentland,et al.  Socially aware, computation and communication , 2005, Computer.

[18]  D. Buss,et al.  Sexual strategies theory: an evolutionary perspective on human mating. , 1993, Psychological review.

[19]  Daniel Gatica-Perez,et al.  A Multimodal Corpus for Studying Dominance in Small Group Conversations , 2010 .

[20]  Gatica-PerezDaniel Automatic nonverbal analysis of social interaction in small groups , 2009 .