@inproceedings{alt16_dis,
title = {Attention, please! Comparing Features for Measuring Audience Attention Towards Pervasive Displays},
author = {Florian Alt and Andreas Bulling and Lukas Mecke and Daniel Buschek},
url = {https://perceptual.mpi-inf.mpg.de/files/2016/04/alt16_dis.pdf},
doi = {10.1145/2901790.2901897},
isbn = {978-1-4503-4031-1},
year = {2016},
date = {2016-06-04},
booktitle = {Proc. of the ACM SIGCHI Conference on Designing Interactive Systems (DIS)},
pages = {823-828},
abstract = {Measuring audience attention towards pervasive displays is important but accurate measurement in real time remains a significant sensing challenge. Consequently, researchers and practitioners typically use other features, such as face presence, as a proxy. We provide a principled comparison of the performance of six features and their combinations for measuring attention: face presence, movement trajectory, walking speed, shoulder orientation, head pose, and gaze direction. We implemented a prototype that is capable of capturing this rich set of features from video and depth camera data. Using a controlled lab experiment (N=18) we show that as a single feature, face presence is indeed among the most accurate. We further show that accuracy can be increased through a combination of features (+10.3%), knowledge about the audience (+63.8%), as well as user identities (+69.0%). Our findings are valuable for display providers who want to collect data on display effectiveness or build interactive, responsive apps.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}