arrow
Return

Cyber-Physical Signage Interacting With Gesture-Based Human-Machine Interfaces Through Mobile Cloud Computing

delete2016-01-01
delete13
delete
OA
AI
L
Lien‐Wu Chen *
Y
Yu‐Fan Ho
M
Ming‐Fong Tsai
H
Hsi‐Min Chen
DOI:10.1109/ACCESS.2016.2594799delete
deleteOriginal
deleteShare
deleteSave
View PDF
Abstract

Abstract

En 中文
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.
Keywords:
Cloud computing
cyber-physical system
human-machine interaction
mobile device
signage interacting
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

IEEE Access cover
IEEE Access
IF:
3.6
Papers:
9.8W
Citations:
29.4W

Organization

F
Feng Chia University
Scholars:
3.4K
Papers: 3.7K
Citations: 2.6K
N
National Chung Cheng University
Scholars:
3.7K
Papers: 3.3K
Citations: 2.0K