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Institutional Repository [SANDBOX]
Technical University of Crete
Technical University of Crete
EN
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EL
| URI | http://purl.tuc.gr/dl/dias/7FDD5AC1-670B-4809-B3A1-E978E064805C | - |
| Identifier | https://doi.org/10.1145/3456875 | - |
| Identifier | https://dl.acm.org/doi/10.1145/3456875 | - |
| Language | en | - |
| Extent | 20 pages | en |
| Title | Eye tracking interaction on unmodified mobile VR headsets using the selfie camera | en |
| Creator | Drakopoulos Panagiotis | en |
| Creator | Δρακοπουλος Παναγιωτης | el |
| Creator | Koulieris Georgios-Alexandros | en |
| Creator | Κουλιερης Γεωργιος-Αλεξανδρος | el |
| Creator | Mania Aikaterini | en |
| Creator | Μανια Αικατερινη | el |
| Publisher | Association for Computing Machinery (ACM) | en |
| Content Summary | Input methods for interaction in smartphone-based virtual and mixed reality (VR/MR) are currently based on uncomfortable head tracking controlling a pointer on the screen. User fixations are a fast and natural input method for VR/MR interaction. Previously, eye tracking in mobile VR suffered from low accuracy, long processing time, and the need for hardware add-ons such as anti-reflective lens coating and infrared emitters. We present an innovative mobile VR eye tracking methodology utilizing only the eye images from the front-facing (selfie) camera through the headset’s lens, without any modifications. Our system first enhances the low-contrast, poorly lit eye images by applying a pipeline of customised low-level image enhancements suppressing obtrusive lens reflections. We then propose an iris region-of-interest detection algorithm that is run only once. This increases the iris tracking speed by reducing the iris search space in mobile devices. We iteratively fit a customised geometric model to the iris to refine its coordinates. We display a thin bezel of light at the top edge of the screen for constant illumination. A confidence metric calculates the probability of successful iris detection. Calibration and linear gaze mapping between the estimated iris centroid and physical pixels on the screen results in low latency, real-time iris tracking. A formal study confirmed that our system’s accuracy is similar to eye trackers in commercial VR headsets in the central part of the headset’s field-of-view. In a VR game, gaze-driven user completion time was as fast as with head-tracked interaction, without the need for consecutive head motions. In a VR panorama viewer, users could successfully switch between panoramas using gaze. | en |
| Type of Item | Peer-Reviewed Journal Publication | en |
| Type of Item | Δημοσίευση σε Περιοδικό με Κριτές | el |
| License | http://creativecommons.org/licenses/by/4.0/ | en |
| Date of Item | 2022-10-31 | - |
| Date of Publication | 2021 | - |
| Subject | Mobile VR | en |
| Subject | Eye tracking | en |
| Bibliographic Citation | P. Drakopoulos, G.-A. Koulieris, and K. Mania, “Eye tracking interaction on unmodified mobile VR headsets using the selfie camera,” ACM Trans. Appl. Percept., vol. 18, no. 3, July 2021, doi: 10.1145/3456875. | en |
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