OBJECTS RECOGNITION AND POSE CALCULATION SYSTEM FOR MOBILE AUGMENTED REALITY USING NATURAL FEATURES - Rehman Ullah, Khan; Shahren, Ahmad Zaidi Adruce; Mohd Shahrizal, Sunar; Yahya, Khan; Yasir Hayat, Mughal (Indian Society for Education and Environment, 2015)
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.