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Computer Science > Human-Computer Interaction

arXiv:2406.00255 (cs)
[Submitted on 1 Jun 2024 (v1), last revised 14 Aug 2024 (this version, v2)]

Title:Measuring eye-tracking accuracy and its impact on usability in apple vision pro

Authors:Zehao Huang, Gancheng Zhu, Xiaoting Duan, Rong Wang, Yongkai Li, Shuai Zhang, Zhiguo Wang
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Abstract:With built-in eye-tracking cameras, the recently released Apple Vision Pro (AVP) mixed reality (MR) headset features gaze-based interaction, eye image rendering on external screens, and iris recognition for device unlocking. One of the technological advancements of the AVP is its heavy reliance on gaze- and gesture-based interaction. However, limited information is available regarding the technological specifications of the eye-tracking capability of the AVP, and raw gaze data is inaccessible to developers. This study evaluates the eye-tracking accuracy of the AVP with two sets of tests spanning both MR and virtual reality (VR) applications. This study also examines how eye-tracking accuracy relates to user-reported usability. The results revealed an overall eye-tracking accuracy of 1.11° and 0.93° in two testing setups, within a field of view (FOV) of approximately 34° x 18°. The usability and learnability scores of the AVP, measured using the standard System Usability Scale (SUS), were 75.24 and 68.26, respectively. Importantly, no statistically reliable correlation was found between eye-tracking accuracy and usability scores. These results suggest that eye-tracking accuracy is critical for gaze-based interaction, but it is not the sole determinant of user experience in VR/AR.
Comments: 16 pages, 6 figures and 3 tables
Subjects: Human-Computer Interaction (cs.HC)
Cite as: arXiv:2406.00255 [cs.HC]
  (or arXiv:2406.00255v2 [cs.HC] for this version)
  https://doi.org/10.48550/arXiv.2406.00255

Submission history

From: Zehao Huang [view email]
[v1] Sat, 1 Jun 2024 01:32:52 UTC (1,467 KB)
[v2] Wed, 14 Aug 2024 06:32:54 UTC (2,472 KB)
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