ARfy

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@inproceedings{10.1145/3526114.3558697,
    author = {Caetano, Arthur and Sra, Misha},
    title = {ARfy: A Pipeline for Adapting 3D Scenes to Augmented Reality},
    year = {2022},
    isbn = {9781450393218},
    publisher = {Association for Computing Machinery},
    address = {New York, NY, USA},
    url = {https://doi.org/10.1145/3526114.3558697},
    doi = {10.1145/3526114.3558697},
    abstract = {Virtual content placement in physical scenes is a crucial aspect of augmented reality (AR). This task is particularly challenging when the virtual elements must adapt to multiple target physical environments unknown during development. AR authors use strategies such as manual placement performed by end-users, automated placement powered by author-defined constraints, and procedural content generation to adapt virtual content to physical spaces. Although effective, these options require human effort or annotated virtual assets. As an alternative, we present ARfy, a pipeline to support the adaptive placement of virtual content from pre-existing 3D scenes in arbitrary physical spaces. ARfy does not require intervention by end-users or asset annotation by AR authors. We demonstrate the pipeline capabilities using simulations on a publicly available indoor space dataset. ARfy makes any generic 3D scene automatically AR-ready and provides evaluation tools to facilitate future research on adaptive virtual content placement.},
    booktitle = {Adjunct Proceedings of the 35th Annual ACM Symposium on User Interface Software and Technology},
    articleno = {11},
    numpages = {3},
    keywords = {3D to AR, adaptive content placement, augmented reality},
    location = {Bend, OR, USA},
    series = {UIST '22 Adjunct}
}