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  • FUSE : towards ai-based future services for generating augmented reality experience
    Čopič Pucihar, Klen ; Geroimenko, Vladimir Aleksandrovich ; Kljun, Matjaž, računalništvo
    This chapter explores the use of Artificial Intelligence (AI) to semantically understand the scene, to decide when to provide Augmented Reality (AR) content or to take other actions, and how to ... generate the augmented content. The chapter presents a survey of novel Machine Learning techniques that have a capability to assist future AI-driven smart AR services and to enable their generalisation to a wide range of scenarios making them ubiquitous, adaptable and robust for realworld usage. The key challenge considered by the authors is how to generalise these techniques to unprepared arbitrary environments in which the scene objects are automatically detected, recognised and segmented in an intelligent way that allows the system to annotate the scene automatically. The chapter begins with an exploration of various methods and techniques which could enable the creation of AR services at such a high level of generalisation. It provides a review of a variety of machine learning algorithms for object detection, recognition and image segmentation. Then, it analyses 3D scene creation and reconstruction, which includes various 3D scanning approaches as well as techniques for generating context aware text and image annotations. Finally, the chapter considers the newest methods of view synthesis using neural networks known as 3D neural rendering and finishes with a discussion about the current and future challenges of AI-based services for generating AR experiences.
    Source: Augmented reality and artificial intelligence : the fusion of advanced technologies (Str. 285-306)
    Type of material - article, component part ; adult, serious
    Publish date - 2023
    Language - english
    COBISS.SI-ID - 153209859

    Link(s):

    https://link.springer.com/content/pdf/10.1007/978-3-031-27166-3_16?pdf=chapter%20toc
    https://doi.org/10.1007/978-3-031-27166-3
    DOI

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