Gupta, A and Jaiswal, R and Adhikari, S and Balasubramanian, Vineeth N
(2016)
DAISEE: Dataset for Affective States in E-Learning Environments.
arXiv.
pp. 1-22.
Abstract
Extracting and understanding a ective states of subjects
through analysis of face videos is of high consequence to advance the
levels of interaction in human-computer interfaces. This paper aims to
highlight vision-related tasks focused on understanding \reactions" of
subjects to presented content which has not been largely studied by the
vision community in comparison to other emotions. To facilitate future
study in this eld, we present an e ort in collecting DAiSEE, a free to
use large-scale dataset using crowd annotation, that not only simulates
a real world setting for e-learning environments, but also captures the
interpretability issues of such a ective states by human annotators. In
addition to the dataset, we present benchmark results based on stan-
dard baseline methods and vote aggregation strategies, thus providing a
springboard for further research.
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