@inproceedings{cc2a15038c6249c1a3cb6591751fe0f5,
title = "OMEG: Oulu multi-pose eye gaze dataset",
abstract = "Data is in a very important position for pattern recognition tasks including eye gaze estimation. In the literature, most researchers used normal face datasets, which are not specifically designed for eye gaze estimation. As a result, it is difficult to obtain fine labeled eye gaze direction. Therefore large datasets with well-defined gaze directions are desired. To facilitate related researches, we collect and establish the Oulu Multi-pose Eye Gaze Dataset. Inspired by the psychological observation that gaze direction is intrinsically linked with the head orientation, we are devoted to a new data set of eye gaze images captured under multiple head poses. It finally results in a dataset containing over 40K images from 50 subjects, who were asked to fixate on 10 special points on screen under different poses respectively. We investigate a new eye gaze estimation approach by using the IGO based description, and compare it with other popular eye gaze estimation approaches to provide the baseline results on our dataset.",
keywords = "Dataset, Eye gaze, Head pose",
author = "Qiuhai He and Xiaopeng Hong and Xiujuan Chai and Jukka Holappa and Guoying Zhao and Xilin Chen and Matti Pietik{\"a}inen",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.; 19th Scandinavian Conference on Image Analysis, SCIA 2015 ; Conference date: 15-06-2015 Through 17-06-2015",
year = "2015",
doi = "10.1007/978-3-319-19665-7\_35",
language = "英语",
isbn = "9783319196640",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "418--427",
editor = "Pedersen, \{Kim S.\} and Paulsen, \{Rasmus R.\}",
booktitle = "Image Analysis - 19th Scandinavian Conference, SCIA 2015, Proceedings",
address = "德国",
}