A Gaze-depth Estimation Technique with an Implicit and Continuous Data Acquisition for OST-HMDs
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Date
2017Author
Lee, Gun A. 
Billinghurst, Mark
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The rapid development of machine learning algorithms can be leveraged for potential software solutions in many domains including techniques for depth estimation of human eye gaze. In this paper, we propose an implicit and continuous data acquisition method for 3D gaze depth estimation for an optical see-Through head mounted display (OST-HMD) equipped with an eye tracker. Our method constantly monitoring and generating user gaze data for training our machine learning algorithm. The gaze data acquired through the eye-tracker include the inter-pupillary distance (IPD) and the gaze distance to the real and virtual target for each eye.
BibTeX
@inproceedings {10.2312:egve.20171364,
booktitle = {ICAT-EGVE 2017 - Posters and Demos},
editor = {Tony Huang and Arindam Dey},
title = {{A Gaze-depth Estimation Technique with an Implicit and Continuous Data Acquisition for OST-HMDs}},
author = {Lee, Youngho and Piumsomboon, Thammathip and Ens, Barrett and Lee, Gun A. and Dey, Arindam and Billinghurst, Mark},
year = {2017},
publisher = {The Eurographics Association},
ISBN = {978-3-03868-052-9},
DOI = {10.2312/egve.20171364}
}
booktitle = {ICAT-EGVE 2017 - Posters and Demos},
editor = {Tony Huang and Arindam Dey},
title = {{A Gaze-depth Estimation Technique with an Implicit and Continuous Data Acquisition for OST-HMDs}},
author = {Lee, Youngho and Piumsomboon, Thammathip and Ens, Barrett and Lee, Gun A. and Dey, Arindam and Billinghurst, Mark},
year = {2017},
publisher = {The Eurographics Association},
ISBN = {978-3-03868-052-9},
DOI = {10.2312/egve.20171364}
}