Proceedings: GI 2007

Robust pixel classification for 3D modeling with structured light

Yi Xu, Daniel Aliaga

Proceedings of Graphics Interface 2007: Montréal, Québec, Canada, 28 - 30 May 2007, 233-240

DOI 10.1145/1268517.1268556

  • BibTex

    author = {Xu, Yi and Aliaga, Daniel},
    title = {Robust pixel classification for 3D modeling with structured light},
    booktitle = {Proceedings of Graphics Interface 2007},
    series = {GI 2007},
    year = {2007},
    issn = {0713-5424},
    isbn = {978-1-56881-337-0},
    location = {Montr{\'e}al, Qu{\'e}bec, Canada},
    pages = {233--240},
    numpages = {8},
    doi = {10.1145/1268517.1268556},
    acmdoi = {10.1145/1268517.1268556},
    publisher = {Canadian Human-Computer Communications Society},
    address = {University of Waterloo, Waterloo, Ontario, Canada},


Modeling 3D objects and scenes is an important part of computer graphics. One approach to modeling is projecting binary patterns onto the scene in order to obtain correspondences and reconstruct a densely sampled 3D model. In such structured light systems, determining whether a pixel is directly illuminated by the projector is essential to decoding the patterns. In this paper, we introduce a robust, efficient, and easy to implement pixel classification algorithm for this purpose. Our method correctly establishes the lower and upper bounds of the possible intensity values of an illuminated pixel and of a non-illuminated pixel. Based on the two intervals, our method classifies a pixel by determining whether its intensity is within one interval and not in the other. Experiments show that our method improves both the quantity of decoded pixels and the quality of the final reconstruction producing a dense set of 3D points, inclusively for complex scenes with indirect lighting effects. Furthermore, our method does not require newly designed patterns; therefore, it can be easily applied to previously captured data.