Calibration-free and deep-learning-based customer gaze direction detection technology based on the YOLOv3-tiny model for smart advertising displays
Author:
Affiliation:
1. Department of Electrical Engineering, National Chung Hsing University, Taichung City, Taiwan (R.O.C.)
Funder
the Ministry of Science and Technology
Publisher
Informa UK Limited
Subject
General Engineering
Link
https://www.tandfonline.com/doi/pdf/10.1080/02533839.2023.2262724
Reference29 articles.
1. i-Riter: Machine learning based novel eye tracking and calibration
2. Convolutional Neural Network-Based Methods for Eye Gaze Estimation: A Survey
3. When I Look into Your Eyes: A Survey on Computer Vision Contributions for Human Gaze Estimation and Tracking
4. Calibration-Free Gaze Zone Estimation Using Convolutional Neural Network
5. Cyber-Physical Signage Interacting With Gesture-Based Human–Machine Interfaces Through Mobile Cloud Computing
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1. Advancements in Gaze Coordinate Prediction Using Deep Learning: A Novel Ensemble Loss Approach;Applied Sciences;2024-06-20
2. Calibration-Free Gaze Estimation by Combination with Hand and Facial Features Detection for Interactive Advertising Display;2024 IEEE International Conference on Consumer Electronics (ICCE);2024-01-06
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