Cyber-Physical Signage Interacting With Gesture-Based Human–Machine Interfaces Through Mobile Cloud Computing
In this paper, we propose a cyber-physical signage interacting framework for the interaction between digital signage and mobile users using smart handheld devices, such as smartphones and tablets. The proposed framework can provide diverse multimedia/feedback services to mobile users interacting wit...
Main Authors: | , , , , |
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Format: | Article |
Language: | English |
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IEEE
2016-01-01
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Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/7524019/ |
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author | Lien-Wu Chen Yu-Fan Ho Ming-Fong Tsai Hsi-Min Chen Chi-Fu Huang |
author_facet | Lien-Wu Chen Yu-Fan Ho Ming-Fong Tsai Hsi-Min Chen Chi-Fu Huang |
author_sort | Lien-Wu Chen |
collection | DOAJ |
description | In this paper, we propose a cyber-physical signage interacting framework for the interaction between digital signage and mobile users using smart handheld devices, such as smartphones and tablets. The proposed framework can provide diverse multimedia/feedback services to mobile users interacting with digital signage through face detection, classification, and recognition techniques based on mobile cloud computing. Mobile users only need to click and drag the interested service over the face of advertising celebrities/endorsers displayed on digital signage and can obtain supplementary multimedia information or feedback related comments. Using the intuitive way of gesture-based operations, mobile users can directly interact with digital signage through their handheld devices. Our framework reveals an innovative human-machine interface for signage interacting between digital signage and mobile users. In addition, we integrate our framework with a face cache mechanism that can make the interaction delay as small as possible for popular signage. Furthermore, an Android-based signage interacting system is implemented to verify the feasibility and superiority of our framework. Experimental results show that our approach outperforms the existing methods and can significantly reduce the average consumption time of obtaining interested multimedia contents from digital signage. |
first_indexed | 2024-12-16T17:45:06Z |
format | Article |
id | doaj.art-3282385f28ea440893cdc8f8780607e8 |
institution | Directory Open Access Journal |
issn | 2169-3536 |
language | English |
last_indexed | 2024-12-16T17:45:06Z |
publishDate | 2016-01-01 |
publisher | IEEE |
record_format | Article |
series | IEEE Access |
spelling | doaj.art-3282385f28ea440893cdc8f8780607e82022-12-21T22:22:30ZengIEEEIEEE Access2169-35362016-01-0143951396010.1109/ACCESS.2016.25947997524019Cyber-Physical Signage Interacting With Gesture-Based Human–Machine Interfaces Through Mobile Cloud ComputingLien-Wu Chen0https://orcid.org/0000-0001-5453-9675Yu-Fan Ho1Ming-Fong Tsai2Hsi-Min Chen3Chi-Fu Huang4Department of Information Engineering and Computer Science, Feng Chia University, Taichung, TaiwanDepartment of Information Engineering and Computer Science, Feng Chia University, Taichung, TaiwanDepartment of Information Engineering and Computer Science, Feng Chia University, Taichung, TaiwanDepartment of Information Engineering and Computer Science, Feng Chia University, Taichung, TaiwanDepartment of Computer Science and Information Engineering, National Chung Cheng University, Chiayi, TaiwanIn this paper, we propose a cyber-physical signage interacting framework for the interaction between digital signage and mobile users using smart handheld devices, such as smartphones and tablets. The proposed framework can provide diverse multimedia/feedback services to mobile users interacting with digital signage through face detection, classification, and recognition techniques based on mobile cloud computing. Mobile users only need to click and drag the interested service over the face of advertising celebrities/endorsers displayed on digital signage and can obtain supplementary multimedia information or feedback related comments. Using the intuitive way of gesture-based operations, mobile users can directly interact with digital signage through their handheld devices. Our framework reveals an innovative human-machine interface for signage interacting between digital signage and mobile users. In addition, we integrate our framework with a face cache mechanism that can make the interaction delay as small as possible for popular signage. Furthermore, an Android-based signage interacting system is implemented to verify the feasibility and superiority of our framework. Experimental results show that our approach outperforms the existing methods and can significantly reduce the average consumption time of obtaining interested multimedia contents from digital signage.https://ieeexplore.ieee.org/document/7524019/Cloud computingcyber-physical systemhuman-machine interactionmobile devicesignage interacting |
spellingShingle | Lien-Wu Chen Yu-Fan Ho Ming-Fong Tsai Hsi-Min Chen Chi-Fu Huang Cyber-Physical Signage Interacting With Gesture-Based Human–Machine Interfaces Through Mobile Cloud Computing IEEE Access Cloud computing cyber-physical system human-machine interaction mobile device signage interacting |
title | Cyber-Physical Signage Interacting With Gesture-Based Human–Machine Interfaces Through Mobile Cloud Computing |
title_full | Cyber-Physical Signage Interacting With Gesture-Based Human–Machine Interfaces Through Mobile Cloud Computing |
title_fullStr | Cyber-Physical Signage Interacting With Gesture-Based Human–Machine Interfaces Through Mobile Cloud Computing |
title_full_unstemmed | Cyber-Physical Signage Interacting With Gesture-Based Human–Machine Interfaces Through Mobile Cloud Computing |
title_short | Cyber-Physical Signage Interacting With Gesture-Based Human–Machine Interfaces Through Mobile Cloud Computing |
title_sort | cyber physical signage interacting with gesture based human x2013 machine interfaces through mobile cloud computing |
topic | Cloud computing cyber-physical system human-machine interaction mobile device signage interacting |
url | https://ieeexplore.ieee.org/document/7524019/ |
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