An efficient and robust mobile augmented reality application

Abstract

Augmented Reality (AR) technology is perceived to be evolved from the foundation of Virtual Reality (VR) technology. The final objective of AR is to offer ubiquitous access and better management to information through the use of seamless techniques in which the interactive computer-generated world is combined with the interactive real world in a coherent environment. The direction of research in the field of AR has been shifted from traditional Desktop based mediums to the mobile devices such as the smartphones. However, image recognition on smartphones executes many challenges and restrictions in the form of robustness and efficiency which are the general performance measurement of image recognition. Smart phones have limited processing capabilities as compared to the PC platform, hence the process of mobile AR application development and use of image recognition algorithm need to be emphasised. The processes of mobile AR application development include detection, description and matching. All the processes and algorithms need to be properly selected in order to create a robust and efficient mobile AR application. The algorithm used in this work for detection, description and matching are AGAST, FREAK and Hamming distance respectively. The computation time, robustness towards rotation, scale and brightness are evaluated. The dataset used to evaluate the mobile AR application is the benchmark dataset; Mikolajczyk. The results showed that the mobile AR application is efficient with a computation time of 29.1ms. The robustness towards scale, rotation and brightness changes of the mobile AR application also obtained high accuracy which is 89.76%, 87.71% and 83.87% respectively. Hence, combination of algorithm AGAST, FREAK and Hamming distance are suitable to create an efficient and robust mobile AR application.