Sensors know which photos are memorable

Soyoung Kim, Kalenzi Asio Evelyn Patra, Auk Kim, Kun Pyo Lee, Aviv Segev, Uichin Lee

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

4 Citations (Scopus)


The goal of this study is to determine if physiological signals are salient in the detection of memorable personal photos. We begin by collecting physiological sensor data as well as memorability and emotion ratings for photos. We then build a mixed model to evaluate the predictive power of physiological variables on memorability and emotion by examining whether or not the photographer's data is useful for predicting the ratings of the photographer or the ratings of the subjects in the photos. Our results suggest that heart rate and GSR (galvanic skin response) data are the major predictors of memorability for photographers, and that the sensor signals are not particularly useful for predicting memorability ratings of subjects in the photos.

Original languageEnglish
Title of host publicationCHI 2017 Extended Abstracts - Proceedings of the 2017 ACM SIGCHI Conference on Human Factors in Computing Systems
Subtitle of host publicationExplore, Innovate, Inspire
PublisherAssociation for Computing Machinery
Number of pages8
ISBN (Electronic)9781450346566
Publication statusPublished - 6 May 2017
Externally publishedYes
Event2017 ACM SIGCHI Conference on Human Factors in Computing Systems, CHI EA 2017 - Denver, United States
Duration: 6 May 201711 May 2017

Publication series

NameConference on Human Factors in Computing Systems - Proceedings
VolumePart F127655


Conference2017 ACM SIGCHI Conference on Human Factors in Computing Systems, CHI EA 2017
Country/TerritoryUnited States


  • Emotion
  • Memorability
  • Memorable photos
  • Physiological data
  • Wearable devices

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design


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