Please use this identifier to cite or link to this item:
http://dx.doi.org/10.18419/opus-13758
Authors: | Jiao, Chuhan Hu, Zhiming Bâce, Mihai Bulling, Andreas |
Title: | SUPREYES: SUPer resolution for EYES using implicit neural representation learning |
Issue Date: | 2023 |
metadata.ubs.publikation.typ: | Konferenzbeitrag |
metadata.ubs.konferenzname: | ACM Symposium on User Interface Software and Technology (36th, 2023, San Francisco, Calif.) |
metadata.ubs.publikation.source: | UIST '23 : proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology. New York, NY : ACM, 2023. - ISBN 979-8-4007-0132-0, Article no. 81 |
URI: | http://nbn-resolving.de/urn:nbn:de:bsz:93-opus-ds-137776 http://elib.uni-stuttgart.de/handle/11682/13777 http://dx.doi.org/10.18419/opus-13758 |
ISBN: | 979-8-4007-0132-0 |
Abstract: | We introduce SUPREYES - a novel self-supervised method to increase the spatio-temporal resolution of gaze data recorded using low(er)-resolution eye trackers. Despite continuing advances in eye tracking technology, the vast majority of current eye trackers - particularly mobile ones and those integrated into mobile devices - suffer from low-resolution gaze data, thus fundamentally limiting their practical usefulness. SUPREYES learns a continuous implicit neural representation from low-resolution gaze data to up-sample the gaze data to arbitrary resolutions. We compare our method with commonly used interpolation methods on arbitrary scale super-resolution and demonstrate that SUPREYES outperforms these baselines by a significant margin. We also test on the sample downstream task of gaze-based user identification and show that our method improves the performance of original low-resolution gaze data and outperforms other baselines. These results are promising as they open up a new direction for increasing eye tracking fidelity as well as enabling new gaze-based applications without the need for new eye tracking equipment. |
Appears in Collections: | 05 Fakultät Informatik, Elektrotechnik und Informationstechnik |
Files in This Item:
File | Description | Size | Format | |
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__SUPer_Resolution_for_EYES_Using_Implicit_Neural_Representation_Learning.pdf | 1,13 MB | Adobe PDF | View/Open |
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