New Potentials of Mixed Reality and its Business Impact

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https://hdl.handle.net/10125/79154

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    Conceptualizing Interactions of Augmented Reality Solutions
    ( 2022-01-04) Bräker, Julia ; Hertel, Julia ; Semmann, Martin
    The rapid evolution of augmented reality has resulted in an ever-increasing number of applications in a wide range of industries and services. Despite this progress, there is still a lack of conceptual understanding of AR interactions and the entire solution space. To bridge this gap, we conceptualize AR solution interactions and provide a comprehensive taxonomy. To represent the state-of-the-art, we build upon an extensive literature review. The resulting taxonomy consists of seven dimensions that encompass 29 characteristics. We contribute to the understanding of AR interactions and, as a result, the applicability of AR solutions in businesses by developing the taxonomy. Likewise, the taxonomy can guide the design of AR solutions as it convincingly describes the solution space.
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    An Efficient Refocusing Scheme for Camera-Array Captured Light Field Video for Improved Visual Immersiveness
    ( 2022-01-04) Mehajabin, Nusrat ; Yan, Peizhi ; Kaur, Supreet ; Song, Jingxiang ; Pourazad, Mahsa T. ; Wang, Yixiao ; Tohidypour, Hamid Reza ; Nasiopoulos, Panos
    Light field video technology attempts to acquire human-like visual data, offering unprecedented immersiveness and a viable path for producing high-quality VR content. Refocusing that is one of the key properties of light field and a must for mixed reality applications has shown to work well for microlens based cameras, but as light field videos acquired by camera arrays have a low angular resolution, the refocused quality suffers. In this paper, we present an approach to improve the visual quality of refocused content captured by a camera array-based setup. Increasing the angular resolution using existing deep learning-based view synthesis method and refocusing the video using shift and sum refocusing algorithm produces over blurring of the in-focus region. Our enhancement method targets these blurry pixels and improves their quality by similarity detection and blending. Experimental results show that the proposed approach achieves better refocusing quality compared to traditional methods.
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