A Survey of the State of Research on Augmented Reality from a Business Perspective using Porter’s Value Chain

In recent years, augmented reality (AR) technology has been able to demonstrate more and more impressively the potential it brings for companies and their valueadding activities, and this even though acceptance of the technology in society is only just beginning. Due to this, our work aims to bring a comprehensive overview of AR deployment opportunities based on the value chain, forcing a symbiosis of potential demonstration and acceptance promotion. For our investigation, we consider the most important peer-reviewed papers on the state of research on augmented reality from a business perspective and provide a comprehensive overview of the different possible uses of AR within a company, structured according to Porter’s value chain, as well as an outlook on future research on the expansion and further development of AR systems. Based on this, we formulate research gaps for future work on AR in the context presented

Registration Combining Wide and Narrow Baseline Feature Tracking Techniques for Markerless AR Systems

Augmented reality (AR) is a field of computer research which deals with the combination of real world and computer generated data. Registration is one of the most difficult problems currently limiting the usability of AR systems. In this paper, we propose a novel natural feature tracking based registration method for AR applications. The proposed method has following advantages: (1) it is simple and efficient, as no man-made markers are needed for both indoor and outdoor AR applications; moreover, it can work with arbitrary geometric shapes including planar, near planar and non planar structures which really enhance the usability of AR systems. (2) Thanks to the reduced SIFT based augmented optical flow tracker, the virtual scene can still be augmented on the specified areas even under the circumstances of occlusion and large changes in viewpoint during the entire process. (3) It is easy to use, because the adaptive classification tree based matching strategy can give us fast and accurate initialization, even when the initial camera is different from the reference image to a large degree. Experimental evaluations validate the performance of the proposed method for online pose tracking and augmentation

Registration based on projective reconstruction technique for augmented reality systems

10.1109/TVCG.2005.48IEEE Transactions on Visualization and Computer Graphics113254-264ITVG