OBJECTS RECOGNITION AND POSE CALCULATION SYSTEM FOR MOBILE AUGMENTED REALITY USING NATURAL FEATURES

Rehman Ullah, Khan and Shahren, Ahmad Zaidi Adruce and Mohd Shahrizal, Sunar and Yahya, Khan and Yasir Hayat, Mughal (2015) OBJECTS RECOGNITION AND POSE CALCULATION SYSTEM FOR MOBILE AUGMENTED REALITY USING NATURAL FEATURES. Indian Journal of Science and Technology, 3 (1). pp. 40-50. ISSN 2321-9262

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Abstract

This study presents a system for real world objects recognition and camera pose estimation from natural features in mobile augmented reality. The system recognizes real world objects in real-time directly without any marker and desktop server. The system extracts natural features by using optimized “Speed up Robust Features” SURF algorithm for mobile architecture. The features are further used by pose estimation algorithm for tracking. This system will provide instant information to smart phone user about real world objects like historical places and products. The experiments show that the formulated algorithms provide stable and accurate registration, robust recognition, and tracking of real world objects from natural features in a speedy, easy, and convenient way on iPhone 4S mobile phon.

Item Type: Article
Uncontrolled Keywords: Mobile Augmented Reality, Natural Features, Objects Recognition, Pose Estimation, Vision-Based Tracking, Mixed Reality and Human Computer Interaction, unimas, university, universiti, Borneo, Malaysia, Sarawak, Kuching, Samarahan, ipta, education, research, Universiti Malaysia Sarawak.
Subjects: H Social Sciences > H Social Sciences (General)
H Social Sciences > HE Transportation and Communications
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Academic Faculties, Institutes and Centres > Faculty of Cognitive Sciences and Human Development
Faculties, Institutes, Centres > Faculty of Cognitive Sciences and Human Development
Academic Faculties, Institutes and Centres > Faculty of Cognitive Sciences and Human Development
Depositing User: Gani
Date Deposited: 18 Nov 2020 07:11
Last Modified: 04 Feb 2022 03:31
URI: http://ir.unimas.my/id/eprint/32774

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