TY - GEN
T1 - Unsupervised clustering of EOG as a viable substitute for optical eye tracking
AU - Flad, Nina
AU - Fomina, Tatiana
AU - Buelthoff, Heinrich H.
AU - Chuang, Lewis L.
N1 - Funding Information:
This research was supported by the Max Planck Society. The authors N.F., H.H.B. and L.L.C. thank the German Research Foundation (DFG) for financial support within project C03 of SFB/Transregio 161.
Publisher Copyright:
© Springer International Publishing AG 2017.
Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.
PY - 2017
Y1 - 2017
N2 - Eye-movements are typically measured with video cameras and image recognition algorithms. Unfortunately, these systems are susceptible to changes in illumination during measurements. Electrooculography (EOG) is another approach for measuring eye-movements that does not suffer from the same weakness. Here, we introduce and compare two methods that allow us to extract the dwells of our participants from EOG signals under presentation conditions that are too difficult for optical eye tracking. The first method is unsupervised and utilizes density-based clustering. The second method combines the optical eye-tracker’s methods to determine fixations and saccades with unsupervised clustering. Our results show that EOG can serve as a sufficiently precise and robust substitute for optical eye tracking, especially in studies with changing lighting conditions. Moreover, EOG can be recorded alongside electroencephalography (EEG) without additional effort.
AB - Eye-movements are typically measured with video cameras and image recognition algorithms. Unfortunately, these systems are susceptible to changes in illumination during measurements. Electrooculography (EOG) is another approach for measuring eye-movements that does not suffer from the same weakness. Here, we introduce and compare two methods that allow us to extract the dwells of our participants from EOG signals under presentation conditions that are too difficult for optical eye tracking. The first method is unsupervised and utilizes density-based clustering. The second method combines the optical eye-tracker’s methods to determine fixations and saccades with unsupervised clustering. Our results show that EOG can serve as a sufficiently precise and robust substitute for optical eye tracking, especially in studies with changing lighting conditions. Moreover, EOG can be recorded alongside electroencephalography (EEG) without additional effort.
UR - http://www.scopus.com/inward/record.url?scp=85012288970&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85012288970&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-47024-5_9
DO - 10.1007/978-3-319-47024-5_9
M3 - Conference contribution
AN - SCOPUS:85012288970
SN - 9783319470238
T3 - Mathematics and Visualization
SP - 151
EP - 167
BT - Eye Tracking and Visualization - Foundations, Techniques, and Applications, ETVIS 2015
A2 - Burch, Michael
A2 - Weiskopf, Daniel
A2 - Fisher, Brian
A2 - Schmidt, Albrecht
A2 - Chuang, Lewis
PB - Springer Heidelberg
T2 - 1st Workshop on Eye Tracking and Visualization, ETVIS 2015
Y2 - 25 October 2015 through 25 October 2015
ER -