@inproceedings{568a987b703046168eb7bee9588f288f,
title = "Where's your mind at? Video-based mind wandering detection during film viewing",
abstract = "Mind wandering (MW) is a ubiquitous phenomenon in which attention involuntarily shifts from task-related processing to taskunrelated thoughts. This study reports preliminary results of a video-based MW detector during film viewing. We collected training data in a study where participants self-reported when they caught themselves MW over the course of watching a 32.5 minute commercial film. We trained classification models on automatically extracted facial features and bodily movement and were able to detect MW with an F1 of .30. The model was successful in reproducing the MW distribution obtained from the self-reports. Copyright is held by the owner/author(s).",
keywords = "Affective computing, Facial features, Film viewing, Mind wandering, User modeling",
author = "Angela Stewart and Huili Chen and Nigel Bosch and Donnelly, {Patrick J.} and D'Mello, {Sidney K.}",
note = "Funding Information: This research was supported by the National Science Foundation (NSF) (DRL 1235958 and IIS 1523091). Any opinions, findings and conclusions, or recommendations expressed in this paper are those of the authors and do not necessarily reflect the views of the NSF.; 24th ACM International Conference on User Modeling, Adaptation, and Personalization, UMAP 2016 ; Conference date: 13-07-2016 Through 17-07-2016",
year = "2016",
month = jul,
day = "13",
doi = "10.1145/2930238.2930266",
language = "English (US)",
series = "UMAP 2016 - Proceedings of the 2016 Conference on User Modeling Adaptation and Personalization",
publisher = "Association for Computing Machinery",
pages = "295--296",
booktitle = "UMAP 2016 - Proceedings of the 2016 Conference on User Modeling Adaptation and Personalization",
address = "United States",
}