Citation

Liew, Jun Xian and Ng, Kok Why and Haw, Su Cheng and Ng, Sew Lai (2022) ARCards: Marker-Based Augmented Reality Recognition for Business Cards. In: 2nd International Conference on Big Data Engineering and Education, BDEE 2022, 5 -7 Aug 2022, Chengdu, China.

Text ARCards_Marker-Based.pdf - Published Version Restricted to Repository staff only Download (1MB)

Abstract

Augmented Reality (AR) is an advanced technology that can improve human life. It provides the users an interactive experience where the real world objects are combined with the computer-generated virtual elements such as sound, video, graphics, GPS overlays and more. This paper surveys on the existing AR applications and also introduces ARCards which is an AR mobile application for business cards using marker-based recognition approach. ARCards is designed to enhance a person's insight view of reality. It changes the users' perception by analyzing and implementing a new way of business card sharing where additional features and functions are well equipped by recognizing the markers on the business card. This could deliver an invaluable experience through AR when introducing a person or a company detail. More valuable contents can be included and displayed as virtual digital information and this is hardly to be fitted into a normal business card. AR markers, are trained to identify as a trigger to output the visual components stored digitally in a database. The main camera in the scene is replaced by ARCamera from Vuforia Engine to recognize the feature markers on a business card and automatically revokes the digital contents from the database to be rendered on the phone scene. Extended tracking is enabled so the users are not required to always place the business card in front of the camera for constantly tracking. The functionalities are combined with the physical world and instantly offer realtime feedback to the users. Recognition process takes less than a second to identify the important features. With ARCards, one can easily stand out from others. ARCards also received 86.7% of users' full satisfaction.

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	Augmented reality, business cards, marker-based tracking, user experience, virtual reality
Subjects:	Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75-76.95 Calculating machines
Divisions:	Faculty of Computing and Informatics (FCI)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	07 Mar 2023 02:04
Last Modified:	07 Mar 2023 02:04
URII:	http://shdl.mmu.edu.my/id/eprint/11204

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