Investigating size personalization for more accurate eye tracking glasses

Yi Yu Hsieh, Chia Chen Liu, Wei Lin Wang, Jen-Hui Chuang*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Personalized eyewear frame could improve the accuracy of eye tracking. To obtain the personalized frame size (temple length), we propose a new measuring instrument that consists of (i) the hardware, a 3D printed trial frame which has marks but no scales, and (ii) the software, a vision-based measurement which is view invariant. The vision-based measurement has accuracy and precision that are both 0.02 cm, while the trial frame can achieve a precision of 0.17 cm for secure wearing. Moreover, dispersion up to 2.56 cm is obtained among the personalized frame sizes for just a fairly small group of users, indicating the importance of having such a personalized measurement system.

Original languageEnglish
Title of host publicationComputer Vision - ACCV 2016 Workshops, ACCV 2016 International Workshops, Revised Selected Papers
EditorsChu-Song Chen, Kai-Kuang Ma, Jiwen Lu
PublisherSpringer Verlag
Pages239-248
Number of pages10
ISBN (Print)9783319545257
DOIs
StatePublished - 1 Jan 2017
Event13th Asian Conference on Computer Vision, ACCV 2016 - Taipei, Taiwan
Duration: 20 Nov 201624 Nov 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10118 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference13th Asian Conference on Computer Vision, ACCV 2016
CountryTaiwan
City Taipei
Period20/11/1624/11/16

Fingerprint Dive into the research topics of 'Investigating size personalization for more accurate eye tracking glasses'. Together they form a unique fingerprint.

  • Cite this

    Hsieh, Y. Y., Liu, C. C., Wang, W. L., & Chuang, J-H. (2017). Investigating size personalization for more accurate eye tracking glasses. In C-S. Chen, K-K. Ma, & J. Lu (Eds.), Computer Vision - ACCV 2016 Workshops, ACCV 2016 International Workshops, Revised Selected Papers (pp. 239-248). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10118 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-54526-4_18