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Textures revisited

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Abstract

We describe texture generation methods for complex objects. Recently developed 3D scanning devices and high-resolution cameras can capture the complex geometry of an object and yield high-resolution images. However, generating a textured model from this input data is still a difficult problem. This task is divided into three subproblems: parameterization, texture combination, and texture restoration. A low-distortion parameterization method is presented, which minimizes geometry stretch energy. Photographs of the object taken from multiple viewpoints under modestly uncontrolled illumination conditions are merged into a seamless texture using our new texture combination method. We also demonstrate a texture restoration method that can fill in missing pixel information when the input photographs do not provide sufficient information to cover the entire surface due to self-occlusion or registration errors. Our methods are fully automatic, except for the registration process between a 3D model and input photographs. We demonstrate the application of our method to human face models for evaluation. The techniques presented in this paper make a consistent and complete pipeline to generate the texture of a complex object.

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Authors and Affiliations

  1. MPI Informatik, Saarbrücken, Germany

    Hitoshi Yamauchi, Jörg Haber & Hans-Peter Seidel

  2. Stanford University, USA

    Hendrik P.A. Lensch

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  1. Hitoshi Yamauchi
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  2. Hendrik P.A. Lensch
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  3. Jörg Haber
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  4. Hans-Peter Seidel
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Correspondence to Hitoshi Yamauchi.

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Yamauchi, H., Lensch, H., Haber, J. et al. Textures revisited. Vis Comput 21, 217–241 (2005). https://doi.org/10.1007/s00371-005-0283-5

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