<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>The visual system has a strong information processing ability, and visual attention tracking has various applications in various scenes. This paper mainly focuses on the sports scene of ice and snow far mobilization. It constructs a visual attention system model based on eye tracking. It first establishes an eye tracking system framework using deep learning, and improves the gaze estimation by optimizing the feature extraction network. The visual attention system model was constructed using particle filtering based on motion feature cognition. In the eye-tracking visual attention system model experiments, the Accuracy of the improved eye-tracking system in this paper can be significantly improved to 1.13°, and the error of the visual attention system can be kept within 10°. Furthermore, the four ice and snow sports scene types have an average accuracy of 85.47%, and the constructed model performs well. This study offers a guide for effectively combining eye tracking technology and visual attention.</p>
</abstract>

The visual system has a strong information processing ability, and visual attention tracking has various applications in various scenes. This paper mainly focuses on the sports scene of ice and snow far mobilization. It constructs a visual attention system model based on eye tracking. It first establishes an eye tracking system framework using deep learning, and improves the gaze estimation by optimizing the feature extraction network. The visual attention system model was constructed using particle filtering based on motion feature cognition. In the eye-tracking visual attention system model experiments, the Accuracy of the improved eye-tracking system in this paper can be significantly improved to 1.13°, and the error of the visual attention system can be kept within 10°. Furthermore, the four ice and snow sports scene types have an average accuracy of 85.47%, and the constructed model performs well. This study offers a guide for effectively combining eye tracking technology and visual attention.

A study of visual attention patterns of snow and ice athletes based on eye-tracking technology

Department of Art and Technology, School of Visual Arts and Design

Department of Visual Communication Design

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

The visual system has a strong information processing ability, and visual attention tracking has various applications in various scenes. This paper mainly...

A study of visual attention patterns of snow and ice athletes based on eye-tracking technology

Online veröffentlicht: 03. Mai 2024

Seitenbereich: -

Eingereicht: 02. Apr. 2024

Akzeptiert: 20. Apr. 2024

DOI: https://doi.org/10.2478/amns-2024-0946

Schlüsselwörter
Deep learning, Eye tracking, Particle filtering, Visual attention, Ice and snow sports

© 2024 Pengyu Liu et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

A study of visual attention patterns of snow and ice athletes based on eye-tracking technology

Online veröffentlicht: 03. Mai 2024

Seitenbereich: -

Eingereicht: 02. Apr. 2024

Akzeptiert: 20. Apr. 2024

DOI: https://doi.org/10.2478/amns-2024-0946

SchlüsselwörterDeep learning, Eye tracking, Particle filtering, Visual attention, Ice and snow sports

© 2024 Pengyu Liu et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Deep learning, Eye tracking, Particle filtering, Visual attention, Ice and snow sports