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

<p>People with disabilities have new and advanced methods to communicate with the applications for virtual keyboards and other communication tools. In this paper, we utilized a novel deep reinforcement learning-based technique for determining the location of the accessible options for gaze-controlled tree-based menu selection system. A virtual English keyboard has been incorporated into the layout of the new user interface, which also includes improved requests for text modification through the gaze. The two methods used to manage the system are: 1) eye tracking for typing on the virtual keyboard and 2) eye tracking with a device for soft-switch utilizing deep reinforcement learning. Simulation results show that DRL based algorithm outperforms other baseline techniques in terms of total loss and accuracy.</p>
</abstract>

People with disabilities have new and advanced methods to communicate with the applications for virtual keyboards and other communication tools. In this paper, we utilized a novel deep reinforcement learning-based technique for determining the location of the accessible options for gaze-controlled tree-based menu selection system. A virtual English keyboard has been incorporated into the layout of the new user interface, which also includes improved requests for text modification through the gaze. The two methods used to manage the system are: 1) eye tracking for typing on the virtual keyboard and 2) eye tracking with a device for soft-switch utilizing deep reinforcement learning. Simulation results show that DRL based algorithm outperforms other baseline techniques in terms of total loss and accuracy.

Gaze Tracking for Hands-Free Human Using Deep Reinforcement Learning Approach

Journal of Smart Internet of Things

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

{"article-title":"Gaze Tracking for Hands-Free Human Using Deep Reinforcement Learning Approach"}

People with disabilities have new and advanced methods to communicate with the applications for virtual keyboards and other communication tools. In this paper,...

Gaze Tracking for Hands-Free Human Using Deep Reinforcement Learning Approach

Publicado en línea: 15 dic 2023

Páginas: 105 - 114

Recibido: 23 ago 2021

Aceptado: 17 sept 2021

DOI: https://doi.org/10.2478/jsiot-2023-0013

Palabras clave
Gaze Tracking, Deep reinforcement learning, Eye gaze, Hands-Free

© 2023 Irfan Ullah et al., published by Sciendo

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

Gaze Tracking for Hands-Free Human Using Deep Reinforcement Learning Approach

Publicado en línea: 15 dic 2023

Páginas: 105 - 114

Recibido: 23 ago 2021

Aceptado: 17 sept 2021

DOI: https://doi.org/10.2478/jsiot-2023-0013

Palabras claveGaze Tracking, Deep reinforcement learning, Eye gaze, Hands-Free

© 2023 Irfan Ullah et al., published by Sciendo

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

Palabras clave
Gaze Tracking, Deep reinforcement learning, Eye gaze, Hands-Free