Implementation of Augmented Reality applications to recognize Automotive Vehicle using Microsoft HoloLens : Performance comparison of Vuforia 3-D recognition and QR-code recognition Microsoft HoloLens applications

Abstract: Context. Volvo Construction Equipment is planning to use Microsoft Hololens as a tool for the on-site manager to keep a track on the automotive machines and obtain their corresponding work information. For that, a miniature site has been build at PDRL BTH consisting of three different automotive vehicles. We are developing Augmented Reality applications for Microsoft Hololens to recognize these automotive vehicles. There is a need to identify the most feasible recognition method that can be implemented using Microsoft Hololens. Objectives. In this study, we investigate which among the Vuforia 3-D recognition method and the feasible method is best suited for the Microsoft Hololens and we also find out the maximum distance at which an automotive vehicle can be recognized by the Microsoft Hololens. Methods. In this study, we conducted a literature review and the number of articles has been reviewed for IEEE Xplore, ACM Digital Library, Google Scholar and Scopus sources. Seventeen articles were selected for review after reading their titles and abstracts of articles obtained from the search. Two experiments were performed to find out the best recognition method of the Microsoft Hololens and the maximum distance at which an automotive vehicle can be recognized by the Microsoft Hololens. Results. QR-code recognition method is the best recognition method to be used by Microsoft Hololens for recognizing automotive vehicles in the range of one to two feet and Vuforia 3-D recognition method is recommended for more than two feet distance. Conclusions. We conclude that the QR-code recognition method is suitable for recognizing vehicles in the close range (1-2 feet) and Vuforia 3-D object recognition is suitable for recognition for distance over two feet. These two methods are different from each other. One used the 3-D scan of the vehicle to recognize the vehicle and the other uses image recognition (using unique QR-codes). We covered effect of distance on the recognition capability of the application and a lot of work has to be done in terms of how does the QR-code size effects the maximum distance at which an automotive vehicle can be recognized. We conclude that there is a need for further experimentation in order to find out the impact of QR-code size on the maximum recognition distance.