@inproceedings{a2e58c6aec114cd6ba8ec5eeab36427b,
title = "Sensors know which photos are memorable",
abstract = "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.",
keywords = "Emotion, Memorability, Memorable photos, Physiological data, Wearable devices",
author = "Soyoung Kim and Patra, {Kalenzi Asio Evelyn} and Auk Kim and Lee, {Kun Pyo} and Aviv Segev and Uichin Lee",
year = "2017",
month = may,
day = "6",
doi = "10.1145/3027063.3053198",
language = "English",
series = "Conference on Human Factors in Computing Systems - Proceedings",
publisher = "Association for Computing Machinery",
pages = "2706--2713",
booktitle = "CHI 2017 Extended Abstracts - Proceedings of the 2017 ACM SIGCHI Conference on Human Factors in Computing Systems",
note = "2017 ACM SIGCHI Conference on Human Factors in Computing Systems, CHI EA 2017 ; Conference date: 06-05-2017 Through 11-05-2017",
}