A New Model for Augmenting Retrieved Context-Based Information to Detected Objects in Augmented Reality

Moradi Shabestari, Maryam; Vahidi Asl, Mojtaba; Abdoos, Monireh

doi:10.48308/jicse.2023.230783.1020

A New Model for Augmenting Retrieved Context-Based Information to Detected Objects in Augmented Reality

Document Type : Original Article

Authors

maryam moradi shabestari ¹

mojtaba Vahidi Asl ²

monireh abdoos ³

¹ دانشکده مهندسی و علوم کامپیوتر دانشگاه شهید بهشتی

² Shahid Beheshti University Faculty of Computer Science and Engineering Software and information systems

³ Shahid Beheshti University Faculty of Computer Science and Engineering artificial intelligence

https://doi.org/10.48308/jicse.2023.230783.1020

Abstract

Augmented reality technology integrates information with the environment in real-time. The capability to add information to objects and interact with users according to their requests can be an enjoyable and useful experience. Most Augmented Reality systems have a fixed static database containing registered objects. To enhance Augmented Reality applications, dynamic information sources can be used. An information source such as the web which has expanded and up-to-date data, could be an appropriate alternative. Using these information sources in real-time enables the use of Augmented Reality on a wider scale.
This paper introduces an Augmented Reality model based on online content is presented. In this research, case studies are human faces and context-based information is a virtual element, i.e., information about the target face. Using web information resources dynamizes the system in a variety of environments. Furthermore, the user interacts with the system through question-answering. Deep learning methods have been used for information retrieval and question-answering. Moreover, Answers to frequently asked questions that are confirmed by users are stored in the database for faster response time.
The experimental results reveal that users can interact with the Augmented Reality system through question-answering and augment the required information with a speed of 0.642 seconds and an F-score of 87.9% on the SQuAD dataset.

Keywords

Augmented Reality

Information Retrieval

Question-Answering

Object Recognition

Subjects