| 1. |
- Niehorster, Diederick C., et al.
(författare)
-
The impact of slippage on the data quality of head-worn eye trackers
- 2020
-
Ingår i: Behavior Research Methods. - : Springer Science and Business Media LLC. - 1554-3528.
-
Tidskriftsartikel (refereegranskat)abstract
- Mobile head-worn eye trackers allow researchers to record eye-movement data as participants freely move around and interact with their surroundings. However, participant behavior may cause the eye tracker to slip on the participant’s head, potentially strongly affecting data quality. To investigate how this eye-tracker slippage affects data quality, we designed experiments in which participants mimic behaviors that can cause a mobile eye tracker to move. Specifically, we investigated data quality when participants speak, make facial expressions, and move the eye tracker. Four head-worn eye-tracking setups were used: (i) Tobii Pro Glasses 2 in 50 Hz mode, (ii) SMI Eye Tracking Glasses 2.0 60 Hz, (iii) Pupil-Labs’ Pupil in 3D mode, and (iv) Pupil-Labs’ Pupil with the Grip gaze estimation algorithm as implemented in the EyeRecToo software. Our results show that whereas gaze estimates of the Tobii and Grip remained stable when the eye tracker moved, the other systems exhibited significant errors (0.8–3.1∘ increase in gaze deviation over baseline) even for the small amounts of glasses movement that occurred during the speech and facial expressions tasks. We conclude that some of the tested eye-tracking setups may not be suitable for investigating gaze behavior when high accuracy is required, such as during face-to-face interaction scenarios. We recommend that users of mobile head-worn eye trackers perform similar tests with their setups to become aware of its characteristics. This will enable researchers to design experiments that are robust to the limitations of their particular eye-tracking setup.
|
|
| 2. |
- Santini, Thiago, et al.
(författare)
-
Get a grip : Slippage-robust and glint-free gaze estimation for real-time pervasive head-mounted eye tracking
- 2019
-
Ingår i: Proceedings - ETRA 2019 : 2019 ACM Symposium On Eye Tracking Research and Applications - 2019 ACM Symposium On Eye Tracking Research and Applications. - New York, NY, USA : ACM. - 9781450367097
-
Konferensbidrag (refereegranskat)abstract
- A key assumption conventionally made by flexible head-mounted eye-tracking systems is often invalid: The eye center does not remain stationary w.r.t. the eye camera due to slippage. For instance, eye-tracker slippage might happen due to head acceleration or explicit adjustments by the user. As a result, gaze estimation accuracy can be significantly reduced. In this work, we propose Grip, a novel gaze estimation method capable of instantaneously compensating for eye-tracker slippage without additional hardware requirements such as glints or stereo eye camera setups. Grip was evaluated using previously collected data from a large scale unconstrained pervasive eye-tracking study. Our results indicate significant slippage compensation potential, decreasing average participant median angular offset by more than 43% w.r.t. a non-slippage-robust gaze estimation method. A reference implementation of Grip was integrated into EyeRecToo, an open-source hardware-agnostic eye-tracking software, thus making it readily accessible for multiple eye trackers (Available at: www.ti.uni-tuebingen.de/perception).
|
|
