DAISEE: Dataset for Affective States in E-Learning Environments

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.

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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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IITH Creators:
IITH CreatorsORCiD
Balasubramanian, Vineeth NUNSPECIFIED
Item Type: Article
Subjects: Computer science > Big Data Analytics
Divisions: Department of Computer Science & Engineering
Depositing User: Team Library
Date Deposited: 14 Sep 2016 06:15
Last Modified: 25 Apr 2018 05:37
URI: http://raiith.iith.ac.in/id/eprint/2748
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