Proceedings: GI 2017

Content and Surface Aware Projection

Long Mai (Portland State University), Hoang Le (Portland State University), Feng Liu (Portland State University)

Proceedings of Graphics Interface 2017: Edmonton, Alberta, 16-19 May 2017, 24 - 32

DOI 10.20380/GI2017.04

  • BibTex

    author = {Mai, Long and Le, Hoang and Liu, Feng},
    title = {Content and Surface Aware Projection},
    booktitle = {Proceedings of Graphics Interface 2017},
    series = {GI 2017},
    year = {2017},
    issn = {0713-5424},
    isbn = {978-0-9947868-2-1},
    location = {Edmonton, Alberta},
    pages = {24 -- 32},
    numpages = {8},
    doi = {10.20380/GI2017.04},
    publisher = {Canadian Human-Computer Communications Society / Soci{\'e}t{\'e} canadienne du dialogue humain-machine},


Image projection is important for many applications in entertainment industry, augmented reality, and computer graphics. However, perceived distortion is often introduced by projection, which is a common problem of a projector system. Compensating such distortion for projection on non-trivial surfaces is often very challenging. In this paper, we propose a novel method to pre-warp the image such that it appears as distortion-free as possible on the surface after projection. Our method estimates a desired optimal warping function via an optimization framework. Specifically, we design an objective energy function that models the perceived distortion in projection results. By taking into account both the geometry of the surface and the image content, our method can produce more visually plausible projection results compared with traditional projector systems. We demonstrate the effectiveness of our method with projection results on a wide variety of images and surface geometries.