Performance evaluation of the gazepoint GP3 eye tracking device based on pupil dilation

Document Type

Conference Proceeding

Publication Date

1-1-2017

Publication Title

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volume

10284 11th International Conference, AC 2017, Held as Part of HCI International 2017, Vancouver, BC, Canada, July 9-14, 2017, Proceedings, Part I

First Page

166

Keywords

Eye tracker performance, Gazepoint, Low-cost eye trackers, Memory load, Power spectral density, Pupil dilation, TEPR

Last Page

175

Abstract

Eye tracking is considered one of the most salient methods to study the cognitive demands of humans in human computer interactive systems, due to the unobtrusiveness, flexibility and the development of inexpensive eye trackers. In this work, we evaluate the applicability of these low cost eyetrackers to study pupillary response to varying memory loads and luminance conditions. Specifically, we examine a low-cost eye tracker, the Gazepoint GP3, and objectively evaluate its ability to differentiate pupil dilation metrics under different cognitive loads and luminance conditions. The classification performance is computed in the form of a receiver operating characteristic (ROC) curve and the results indicate that Gazepoint provides a reliable eye tracker to human computer interaction applications requiring pupil dilation studies.

DOI

10.1007/978-3-319-58628-1_14

ISSN

03029743

E-ISSN

16113349

Link to Full Text

Share

COinS