The Science and Information (SAI) Organization
  • Home
  • About Us
  • Journals
  • Conferences
  • Contact Us

Publication Links

  • IJACSA
  • Author Guidelines
  • Publication Policies
  • Outstanding Reviewers

IJACSA

  • About the Journal
  • Call for Papers
  • Editorial Board
  • Author Guidelines
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Fees/ APC
  • Reviewers
  • Apply as a Reviewer

IJARAI

  • About the Journal
  • Archives
  • Indexing & Archiving

Special Issues

  • Home
  • Archives
  • Proposals
  • ICONS_BA 2025

Computer Vision Conference (CVC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Computing Conference

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Intelligent Systems Conference (IntelliSys)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Future Technologies Conference (FTC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact
  • Home
  • Call for Papers
  • Editorial Board
  • Guidelines
  • Submit
  • Current Issue
  • Archives
  • Indexing
  • Fees
  • Reviewers
  • RSS Feed

DOI: 10.14569/IJACSA.2022.0131162
PDF

A Review of Lightweight Object Detection Algorithms for Mobile Augmented Reality

Author 1: Mohammed Mansoor Nafea
Author 2: Siok Yee Tan
Author 3: Mohammed Ahmed Jubair
Author 4: Mustafa Tareq Abd

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 13 Issue 11, 2022.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: Augmented Reality (AR) has led to several technologies being at the forefront of innovation and change in every sector and industry. Accelerated advances in Computer Vision (CV), AR, and object detection refined the process of analyzing and comprehending the environment. Object detection has recently drawn a lot of attention as one of the most fundamental and difficult computer vision topics. The traditional object detection techniques are fully computer-based and typically need massive Graphics Processing Unit (GPU) power, while they aren't usually real-time. However, an AR application required real-time superimposed digital data to enable users to improve their field of view. This paper provides a comprehensive review of most of the recent lightweight object detection algorithms that are suitable to be used in AR applications. Four sources including Web of Science, Scopus, IEEE Xplore, and ScienceDirect were included in this review study. A total of ten papers were discussed and analyzed from four perspectives: accuracy, speed, small object detection, and model size. Several interesting challenges are discussed as recommendations for future work in the object detection field.

Keywords: Augmented reality (AR); object detection; computer vision (CV); non-graphics processing unit (Non-GPU); real time

Mohammed Mansoor Nafea, Siok Yee Tan, Mohammed Ahmed Jubair and Mustafa Tareq Abd. “A Review of Lightweight Object Detection Algorithms for Mobile Augmented Reality”. International Journal of Advanced Computer Science and Applications (IJACSA) 13.11 (2022). http://dx.doi.org/10.14569/IJACSA.2022.0131162

@article{Nafea2022,
title = {A Review of Lightweight Object Detection Algorithms for Mobile Augmented Reality},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.0131162},
url = {http://dx.doi.org/10.14569/IJACSA.2022.0131162},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {11},
author = {Mohammed Mansoor Nafea and Siok Yee Tan and Mohammed Ahmed Jubair and Mustafa Tareq Abd}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

IJACSA

Upcoming Conferences

Computer Vision Conference (CVC) 2026

21-22 May 2026

  • Amsterdam, The Netherlands

Computing Conference 2026

9-10 July 2026

  • London, United Kingdom

Artificial Intelligence Conference 2026

3-4 September 2026

  • Amsterdam, The Netherlands

Future Technologies Conference (FTC) 2026

15-16 October 2026

  • Berlin, Germany
The Science and Information (SAI) Organization
BACK TO TOP

Computer Science Journal

  • About the Journal
  • Call for Papers
  • Submit Paper
  • Indexing

Our Conferences

  • Computer Vision Conference
  • Computing Conference
  • Intelligent Systems Conference
  • Future Technologies Conference

Help & Support

  • Contact Us
  • About Us
  • Terms and Conditions
  • Privacy Policy

The Science and Information (SAI) Organization Limited is a company registered in England and Wales under Company Number 8933205.