Power-efficient and Shift-robust Eye-tracking Sensor for Portable VR Headsets

Katrychuk, Dmytro; Griffith, Henry; Komogortsev, Oleg

Power-efficient and Shift-robust Eye-tracking Sensor for Portable VR Headsets

dc.contributor.author	Katrychuk, Dmytro
dc.contributor.author	Griffith, Henry
dc.contributor.author	Komogortsev, Oleg
dc.date.accessioned	2019-03-29T14:50:30Z
dc.date.available	2019-03-29T14:50:30Z
dc.date.issued	2019-06
dc.description.abstract	This repository contains both the complete data sets and supporting code base from the paper entitled "Power-efficient and shift-robust eye-tracking sensor for portable VR headsets," which as been accepted in the Proceedings of the 2019 ACM Symposium On Eye Tracking Research & Applications (ETRA). Full details regarding the contents of each directory and instructions for preparing the processing environment are provided in the "README.md" file, which is contained within the code base directory. The up-to-date codebase is available on GitHub: https://github.com/pseudowolfvn/psog_nn/tree/etra2019
dc.description.department	Computer Science
dc.description.sponsorship	National Science Foundation, Google
dc.format.medium	1 file (.pdf)
dc.format.medium	3 files (.zip)
dc.identifier.citation	Katrychuk, D., Griffith, H. K., & Komogortsev, O. V. (2019). Power-efficient and shift-robust eye-tracking sensor for portable VR headsets. Proceedings of the ACM Symposium on Eye Tracking Research & Applications (ETRA), Denver, CO.
dc.identifier.doi	https://doi.org/10.1145/3314111.3319821
dc.identifier.uri	https://hdl.handle.net/10877/7955
dc.language.iso	en
dc.publisher	Association for Computing Machinery
dc.source	ACM Symposium on Eye Tracking Research & Applications (ETRA), 2019, Denver, Colorado, United States.
dc.subject	machine learning
dc.subject	photosensor oculography
dc.subject	eye tracking
dc.subject	virtual reality
dc.subject	Computer Science
dc.title	Power-efficient and Shift-robust Eye-tracking Sensor for Portable VR Headsets
dc.type	Dataset