Eye movement data analysis plays an important role in examining human cognitive processes and perceptions. Such analysis at times needs data recording from additional sources too during experiments. In this paper, we study a pair programming based collaboration using two eye trackers, stimulus recording, and an external camera recording. To analyze the collected data, we introduce the EyeSAC system that synchronizes the data from different sources and that removes the noisy and missing gazes from eye tracking data with the help of visual feedback from the external recording. The synchronized and cleaned data is further annotated using our system and then exported for further analysis.
%0 Conference Paper
%1 10.1145/3379157.3391988
%A Kumar, Ayush
%A Mohanty, Debesh
%A Kurzhals, Kuno
%A Beck, Fabian
%A Weiskopf, Daniel
%A Mueller, Klaus
%B ACM Symposium on Eye Tracking Research and Applications
%C New York, NY, USA
%D 2020
%I Association for Computing Machinery
%K visus:weiskopf b01 sfbtrr161 from:christinawarren 2020
%R 10.1145/3379157.3391988
%T Demo of the EyeSAC System for Visual Synchronization, Cleaning, and Annotation of Eye Movement Data
%U https://doi.org/10.1145/3379157.3391988
%X Eye movement data analysis plays an important role in examining human cognitive processes and perceptions. Such analysis at times needs data recording from additional sources too during experiments. In this paper, we study a pair programming based collaboration using two eye trackers, stimulus recording, and an external camera recording. To analyze the collected data, we introduce the EyeSAC system that synchronizes the data from different sources and that removes the noisy and missing gazes from eye tracking data with the help of visual feedback from the external recording. The synchronized and cleaned data is further annotated using our system and then exported for further analysis.
%@ 9781450371353
@inproceedings{10.1145/3379157.3391988,
abstract = {Eye movement data analysis plays an important role in examining human cognitive processes and perceptions. Such analysis at times needs data recording from additional sources too during experiments. In this paper, we study a pair programming based collaboration using two eye trackers, stimulus recording, and an external camera recording. To analyze the collected data, we introduce the EyeSAC system that synchronizes the data from different sources and that removes the noisy and missing gazes from eye tracking data with the help of visual feedback from the external recording. The synchronized and cleaned data is further annotated using our system and then exported for further analysis.},
added-at = {2021-06-16T11:10:56.000+0200},
address = {New York, NY, USA},
articleno = {4},
author = {Kumar, Ayush and Mohanty, Debesh and Kurzhals, Kuno and Beck, Fabian and Weiskopf, Daniel and Mueller, Klaus},
biburl = {https://puma.ub.uni-stuttgart.de/bibtex/26eb446e0c7dfce87f67e6a502a60c539/sfbtrr161},
booktitle = {ACM Symposium on Eye Tracking Research and Applications},
doi = {10.1145/3379157.3391988},
interhash = {0dfb524d5057f46bc6c2a8c8665c4ee1},
intrahash = {6eb446e0c7dfce87f67e6a502a60c539},
isbn = {9781450371353},
keywords = {visus:weiskopf b01 sfbtrr161 from:christinawarren 2020},
location = {Stuttgart, Germany},
numpages = {3},
publisher = {Association for Computing Machinery},
series = {ETRA '20 Adjunct},
timestamp = {2021-06-16T09:10:56.000+0200},
title = {Demo of the EyeSAC System for Visual Synchronization, Cleaning, and Annotation of Eye Movement Data},
url = {https://doi.org/10.1145/3379157.3391988},
year = 2020
}