15-12-2025
جامعة الملك عبدالعزيز
KING ABDULAZIZ UNIVERSITY
Faculty of Computing and Information Technology in Rabigh
Document Details
Document Type
:
Article In Journal
Document Title
:
Fast Markerless Tracking for Augmented Reality in Planar Environment
Fast Markerless Tracking for Augmented Reality in Planar Environment
Subject
:
Computer Science
Document Language
:
English
Abstract
:
Markerless tracking for augmented reality should not only be accurate but also fast enough to provide a seamless synchronization between real and virtual beings. Current reported methods showed that a vision-based tracking is accurate but requires high computational power. This paper proposes a real-time hybrid-based method for tracking unknown environments in markerless augmented reality. The proposed method provides collaboration of vision-based approach with accelerometers and gyroscopes sensors as camera pose predictor. To align the augmentation relative to camera motion, the tracking method is done by substituting feature-based camera estimation with combination of inertial sensors with complementary filter to provide more dynamic response. The proposed method managed to track unknown environment with. faster processing time compared to available feature based approaches. Moreover, the proposed method can sustain its estimation in a situation where feature based tracking loses its track. The collaboration of sensor tracking managed to perform the task for about 22.97 FPS, up to five times faster than feature-based tracking method used as comparison. Therefore, the proposed method can be used to track unknown environments without depending on amount of features on scene, while requiring lower computational cost
ISSN
:
2092-6731
Journal Name
:
3D Research
Volume
:
6
Issue Number
:
4
Publishing Year
:
1436 AH
2015 AD
Article Type
:
Article
Added Date
:
Monday, March 7, 2016
Researchers
Researcher Name (Arabic)
Researcher Name (English)
Researcher Type
Dr Grade
Email
احمد هيرول باسوري
Basori, Ahmad Hoirul
Investigator
Doctorate
abasori@kau.edu.sa
Files
File Name
Type
Description
38342.pdf
pdf
Back To Researches Page