Mobile Device Eye Tracking on Dynamic Visual Contents using Edge Computing and Deep Learning-Reference-Cited by-同舟云学术

Mobile Device Eye Tracking on Dynamic Visual Contents using Edge Computing and Deep Learning

Published:2022-06-08 Issue: Volume: Page:
ISSN:
Container-title:2022 Symposium on Eye Tracking Research and Applications
language:
Short-container-title:

Author:

Gunawardena Nishan¹,Ginige Anupama¹,Javadi Bahman¹,Lui Gough²

Affiliation:

1. School of Computer, Data and Mathematical Sciences, Western Sydney University, Australia

2. The MARCS Institute for Brain, Behaviour and Development, Western Sydney University, Australia

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3517031.3532198

Reference14 articles.

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2. Alexandra Frischen , Andrew P Bayliss , and Steven P Tipper . 2007. Gaze cueing of attention: visual attention, social cognition, and individual differences.Psychological bulletin 133, 4 ( 2007 ), 694. Alexandra Frischen, Andrew P Bayliss, and Steven P Tipper. 2007. Gaze cueing of attention: visual attention, social cognition, and individual differences.Psychological bulletin 133, 4 (2007), 694.

3. Assessing surgeons' skill level in laparoscopic cholecystectomy using eye metrics

4. Andrew G Howard , Menglong Zhu , Bo Chen , Dmitry Kalenichenko , Weijun Wang , Tobias Weyand , Marco Andreetto , and Hartwig Adam . 2017 . Mobilenets: Efficient convolutional neural networks for mobile vision applications. arXiv preprint arXiv:1704.04861(2017). Andrew G Howard, Menglong Zhu, Bo Chen, Dmitry Kalenichenko, Weijun Wang, Tobias Weyand, Marco Andreetto, and Hartwig Adam. 2017. Mobilenets: Efficient convolutional neural networks for mobile vision applications. arXiv preprint arXiv:1704.04861(2017).

5. Eye Tracking for Everyone

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