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Marcus Nyström
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2020 – today
- 2024
- [j5]Virmarie Maquiling, Sean Anthony Byrne, Diederick C. Niehorster, Marcus Nyström, Enkelejda Kasneci:
Zero-Shot Segmentation of Eye Features Using the Segment Anything Model (SAM). Proc. ACM Comput. Graph. Interact. Tech. 7(2): 26:1-26:16 (2024) - 2023
- [c9]Virmarie Maquiling, Sean Anthony Byrne, Marcus Nyström, Enkelejda Kasneci, Diederick C. Niehorster:
V-ir-Net: A Novel Neural Network for Pupil and Corneal Reflection Detection trained on Simulated Light Distributions. MobileHCI (Companion) 2023: 23:1-23:7 - [i3]Sean Anthony Byrne, Marcus Nyström, Virmarie Maquiling, Enkelejda Kasneci, Diederick C. Niehorster:
Precise localization of corneal reflections in eye images using deep learning trained on synthetic data. CoRR abs/2304.05673 (2023) - [i2]Sean Anthony Byrne, Virmarie Maquiling, Marcus Nyström, Enkelejda Kasneci, Diederick C. Niehorster:
LEyes: A Lightweight Framework for Deep Learning-Based Eye Tracking using Synthetic Eye Images. CoRR abs/2309.06129 (2023) - [i1]Virmarie Maquiling, Sean Anthony Byrne, Diederick C. Niehorster, Marcus Nyström, Enkelejda Kasneci:
Zero-Shot Segmentation of Eye Features Using the Segment Anything Model (SAM). CoRR abs/2311.08077 (2023)
2010 – 2019
- 2018
- [c8]Diederick C. Niehorster, Marcus Nyström:
Microsaccade detection using pupil and corneal reflection signals. ETRA 2018: 57:1-57:5 - [c7]William Rosengren, Marcus Nyström, Björn Hammar, Martin Stridh:
Suitability of calibration polynomials for eye-tracking data with simulated fixation inaccuracies. ETRA 2018: 66:1-66:5 - 2015
- [j4]Linnéa Larsson, Marcus Nyström, Richard Andersson, Martin Stridh:
Detection of fixations and smooth pursuit movements in high-speed eye-tracking data. Biomed. Signal Process. Control. 18: 145-152 (2015) - 2014
- [c6]Mona Holmqvist Olander, Eva Wennås Brante, Marcus Nyström:
The Image of Images as an Aid to Improve Learning - An Eye-tracking Experiment Studying the Effect of Contrasts in Computer-based Learning Material. CSEDU (2) 2014: 309-316 - [c5]Linnéa Larsson, Marcus Nyström, Martin Stridh:
Discrimination of fixations and smooth pursuit movements in high-speed eye-tracking data. EMBC 2014: 3797-3800 - [c4]Linnéa Larsson, Marcus Nyström, Andrea Schwaller, Martin Stridh, Kenneth Holmqvist:
Compensation of head movements in mobile eye-tracking data using an inertial measurement unit. UbiComp Adjunct 2014: 1161-1167 - 2013
- [j3]Linnéa Larsson, Marcus Nyström, Martin Stridh:
Detection of Saccades and Postsaccadic Oscillations in the Presence of Smooth Pursuit. IEEE Trans. Biomed. Eng. 60(9): 2484-2493 (2013) - 2012
- [c3]Kenneth Holmqvist, Marcus Nyström, Fiona Bríd Mulvey:
Eye tracker data quality: what it is and how to measure it. ETRA 2012: 45-52 - 2010
- [j2]Marcus Nyström, Kenneth Holmqvist:
Effect of compressed offline foveated video on viewing behavior and subjective quality. ACM Trans. Multim. Comput. Commun. Appl. 6(1): 4:1-4:14 (2010) - [c2]Halszka Jarodzka, Kenneth Holmqvist, Marcus Nyström:
A vector-based, multidimensional scanpath similarity measure. ETRA 2010: 211-218
2000 – 2009
- 2008
- [b1]Marcus Nyström:
Off-line Foveated Compression and Scene Perception: An Eye-Tracking Approach. Lund University, Sweden, 2008 - 2007
- [j1]Marcus Nyström, Kenneth Holmqvist:
Deriving and evaluating eye-tracking controlled volumes of interest for variable-resolution video compression. J. Electronic Imaging 16(1): 013006 (2007) - [c1]Marcus Nyström, Kenneth Holmqvist:
Variable resolution images and their effects on eye movements during free viewing. Human Vision and Electronic Imaging 2007: 649216
Coauthor Index
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