ML Anthology

Physically-Based Augmentation of Real Objects with Virtual Content Under the Influence of Ambient Light

Christoffer Menk, Reinhard Koch
CVPRW 2010 pp. 25-32
doi:10.1109/CVPRW.2010.5543472 /cvprw/2010/menk2010cvprw-physicallybased/

Abstract

In this article, we introduce a new method for the augmentation of a real object with virtual content under the influence of ambient light. For this purpose, we use a physically-based simulation and spectral data which is recorded separately for each of the components: projector, ambient light and real object. Then the simulation computes the influence of every component to the scene and uses the results to compute an adjusted virtual content, which can then be displayed by a real projector in the given situation. The adjustment of the projection can therefore be computed by considering the full dynamic range of the scene and that of the virtual content. Additionally, the virtual content is visualized with informations from the environment and therefore hidden objects or reflections can be integrated into the projection. The proposed methods and the physically-based simulation are validated and visualized through different experiments.

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Cite

Text

Menk and Koch. "Physically-Based Augmentation of Real Objects with Virtual Content Under the Influence of Ambient Light." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2010. doi:10.1109/CVPRW.2010.5543472

Markdown

[Menk and Koch. "Physically-Based Augmentation of Real Objects with Virtual Content Under the Influence of Ambient Light." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2010.](https://mlanthology.org/cvprw/2010/menk2010cvprw-physicallybased/) doi:10.1109/CVPRW.2010.5543472

BibTeX

@inproceedings{menk2010cvprw-physicallybased,
  title     = {{Physically-Based Augmentation of Real Objects with Virtual Content Under the Influence of Ambient Light}},
  author    = {Menk, Christoffer and Koch, Reinhard},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  year      = {2010},
  pages     = {25-32},
  doi       = {10.1109/CVPRW.2010.5543472},
  url       = {https://mlanthology.org/cvprw/2010/menk2010cvprw-physicallybased/}
}