@inproceedings{0799077f411343fe9aac4e2b38c6dee3,
title = "HPCGen: Hierarchical K-Means Clustering and Level Based Principal Components for Scan Path Genaration",
abstract = "In this paper, we present a new approach for decomposing scan paths and its utility for generating new scan paths. For this purpose, we use the K-Means clustering procedure to the raw gaze data and subsequently iteratively to find more clusters in the found clusters. The found clusters are grouped for each level in the hierarchy, and the most important principal components are computed from the data contained in them. Using this tree hierarchy and the principal components, new scan paths can be generated that match the human behavior of the original data. We show that this generated data is very useful for generating new data for scan path classification but can also be used to generate fake scan paths. Code can be downloaded here https://atreus.informatik.uni-tuebingen.de/seafile/d/8e2ab8c3fdd444e1a135/?p=%2FHPCGen&mode=list.",
keywords = "Classification, Dynamic Stimulus, Eye Tracking, Fixed Stimulus, Gaze, Gaze Behaviour, Gaze Simulator, Gaze generation, Scan path, Scan path generation",
author = "Wolfgang Fuhl and Enkelejda Kasneci",
note = "Publisher Copyright: {\textcopyright} 2022 ACM.; 2022 ACM Symposium on Eye Tracking Research and Applications, ETRA 2022 ; Conference date: 08-06-2022 Through 11-06-2022",
year = "2022",
month = jun,
day = "8",
doi = "10.1145/3517031.3529625",
language = "English",
series = "Eye Tracking Research and Applications Symposium (ETRA)",
publisher = "Association for Computing Machinery",
editor = "Spencer, {Stephen N.}",
booktitle = "Proceedings - ETRA 2022",
}