Comparison of Eye-gaze Detection using CNN and Vision Transformer

被引：0

作者：

Niikura D. ^{[1
]}

Abe K. ^{[1
]}

机构：

[1] Graduate School of System Design and Technology, Tokyo Denki University, 5, Senjuasahicho, Adachi-ku, Tokyo

来源：

IEEJ Transactions on Electronics, Information and Systems | 2024年 / 144卷 / 07期

关键词：

convolutional neural network; eye-gaze detection; eye-gaze input; input interface; Vision Transformer;

D O I：

10.1541/ieejeiss.144.683

中图分类号：

TN911 [通信理论];

学科分类号：

081002 ;

摘要：

We propose an eye-gaze input system that utilizes a laptop PC and its inner camera. This system can discriminate the user's eye-gaze direction by using Convolutional Neural Network (CNN) or Vision Transformer (ViT). In this paper, we present the results of a comparison of the newly created eye-gaze direction discrimination model of ViT and the past model created by a CNN. We evaluated the accuracy of discrimination models created by ViT and CNN through the experiments. As a result, the ViT model has higher accuracy than the CNN model in discriminating the center direction. © 2024 The Institute of Electrical Engineers of Japan.

引用

页码：683 / 684

页数：1

共 50 条

[31] Hand gestures recognition using edge computing system based on vision transformer and lightweight CNN
Gupta K.
Singh A.
Yeduri S.R.
Srinivas M.B.
Cenkeramaddi L.R.
[J]. Journal of Ambient Intelligence and Humanized Computing, 2023, 14 (03) : 2601 - 2615
[32] Transportation Mode Detection Combining CNN and Vision Transformer with Sensors Recalibration Using Smartphone Built-In Sensors
Tian, Ye
Hettiarachchi, Dulmini
Kamijo, Shunsuke
[J]. SENSORS, 2022, 22 (17)
[33] Sensing and controlling model for eye-gaze input human-computer interface
Tu, DW
Zhao, QJ
Yin, HR
[J]. OPTICAL MODELING AND PERFORMANCE PREDICTIONS, 2003, 5178 : 221 - 228
[34] Generating Attention Maps from Eye-gaze for the Diagnosis of Alzheimer's Disease
Antunes, Carlos
Silveira, Margarida
[J]. GAZE MEETS MACHINE LEARNING WORKSHOP, VOL 210, 2022, 210 : 3 - 19
[35] Human-computer interaction models and their application in an eye-gaze input system
Zhao, QJ
Tu, DW
Gao, DM
Wang, RS
[J]. PROCEEDINGS OF THE 2004 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7, 2004, : 2274 - 2278
[36] Fire detection using vision transformer on power plant
Zhang, Kaidi
Wang, Binjun
Tong, Xin
Liu, Keke
[J]. ENERGY REPORTS, 2022, 8 : 657 - 664
[37] ViTSigat: Early Black Sigatoka Detection in Banana Plants Using Vision Transformer
Charco, Jorge L.
Yanza-Montalvan, Angela
Zumba-Gamboa, Johanna
Alonso-Anguizaca, Jose
Basurto-Cruz, Edgar
[J]. INFORMATION AND COMMUNICATION TECHNOLOGIES, TICEC 2024, 2025, 2273 : 117 - 130
[38] Smoke detection in foggy surveillance environment using parallel vision transformer network
Shubhangi Chaturvedi
Poornima Singh Thakur
Pritee Khanna
Aparajita Ojha
[J]. Neural Computing and Applications, 2024, 36 (31) : 19499 - 19514
[39] A Novel Hybrid Vision Transformer CNN for COVID-19 Detection from ECG Images
Naidji, Mohamed Rami
Elberrichi, Zakaria
[J]. COMPUTERS, 2024, 13 (05)
[40] Comparison of the Performance of Convolutional Neural Networks and Vision Transformer-Based Systems for Automated Glaucoma Detection with Eye Fundus Images
Alayon, Silvia
Hernandez, Jorge
Fumero, Francisco J.
Sigut, Jose F.
Diaz-Aleman, Tinguaro
[J]. APPLIED SCIENCES-BASEL, 2023, 13 (23):

← 1 2 3 4 5 →