Kit Yung Lam, Lik Hang Lee, and Pan Hui. 2021. A2W: Context-Aware Recommendation System for Mobile Augmented Reality Web Browser. Proceedings of the 29th ACM International Conference on Multimedia. Association for Computing Machinery, New York, NY, USA, 2447–2455. DOI:https://doi.org/10.1145/3474085.3475413
A2W : context-aware recommendation system for mobile augmented RealityWeb browser
|Author:||Lam, Kit Yung1; Lee, Lik Hang2; Hui, Pan3|
1HKUST, Hong Kong SAR
2KAIST and University of Oulu, Republic of Korea
3HKUST and University of Helsinki, Hong Kong SAR
|Online Access:||PDF Full Text (PDF, 5.7 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2022022520832
Association for Computing Machinery,
|Publish Date:|| 2022-02-25
Augmented Reality (AR) offers new capabilities for blurring the boundaries between physical reality and digital media. However, the capabilities of integrating web contents and AR remain underexplored. This paper presents an AR web browser with an integrated context-aware AR-to-Web content recommendation service named as A2W browser, to provide continuously user-centric web browsing experiences driven by AR headsets. We implement the A2W browser on an AR headset as our demonstration application, demonstrating the features and performance of A2W framework. The A2W browser visualizes the AR-driven web contents to the user, which is suggested by the content-based filtering model in our recommendation system. In our experiments, 20 participants with the adaptive UIs and recommendation system in A2W browser achieve up to 30.69% time saving compared to smartphone conditions. Accordingly, A2W-supported web browsing on workstations facilitates the recommended information leading to 41.67% faster reaches to the target information than typical web browsing.
|Pages:||2447 - 2455|
Proceedings of the 29th ACM International Conference on Multimedia. Association for Computing Machinery, MM 2021
ACM International Conference on Multimedia
|Type of Publication:||
A4 Article in conference proceedings
|Field of Science:||
213 Electronic, automation and communications engineering, electronics
This research has been supported in part by 5G-VIIMA and REBOOT Finland IoT Factory projects funded by Business Finland, the 6G Flagship project, the 5GEAR project (Decision No. 318927) and the FIT project (Decision No. 325570) funded by the Academy of Finland, and project 16214817 from the Research Grants Council of Hong Kong.
|Academy of Finland Grant Number:||
318927 (Academy of Finland Funding decision)
© 2021 Association for Computing Machinery.