“Constrained segmentation of complex models for image-based texture editing” by Boier-Martin, Rushmeier and Giantisco

  • ©Ioana Boier-Martin, Holly E. Rushmeier, and Richard Giantisco

  • ©Ioana Boier-Martin, Holly E. Rushmeier, and Richard Giantisco

  • ©Ioana Boier-Martin, Holly E. Rushmeier, and Richard Giantisco

  • ©Ioana Boier-Martin, Holly E. Rushmeier, and Richard Giantisco

  • ©Ioana Boier-Martin, Holly E. Rushmeier, and Richard Giantisco

  • ©Ioana Boier-Martin, Holly E. Rushmeier, and Richard Giantisco

Conference:


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Title:

    Constrained segmentation of complex models for image-based texture editing

Session/Category Title:   Texture


Presenter(s)/Author(s):



Abstract:


    We present a constrained segmentation method for the partitioning of complex textured 3D models. Our method automatically identifies large regions of reduced metric distortion suitable for texture mapping. The boundaries of the regions conform to salient features of the model and respect user-imposed constraints. We illustrate the application of this method to virtual paint restoration through image-based texture editing.

References:


    Bernardini, F., and Rushmeier, H. 2002. The 3D model acquisition pipeline. Computer Graphics Forum 21, 2, 149–172.
    Macqueeen, J. 1967. Some methods for classification and analysis of multivariate observations. In Proc. 5th Berkeley Symp. Math Statistics and Prob., 281–297.


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