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Texture map generation for 3D reconstructed scenes

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Abstract

We present a novel method for generating texture maps for 3D geometric models reconstructed using consumer RGB-D sensors. Our method generates a texture map for a simplified 3D mesh of the reconstructed scene using spatially and temporally sub-sampled key frames of the input RGB stream. We acquire an accurate texture map by optimizing the texture coordinates of the 3D model to maximize the photometric consistency among multiple key frames. We show that the optimization can be performed efficiently using GPU by exploiting the locality of texture coordinate manipulation. Experimental results demonstrate that our method can generate a texture map in a few tens of seconds for a large 3D model, such as a whole room.

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Acknowledgments

This work was supported by the National Research Foundation of Korea (NRF) Grant (NRF-2014R1A2A1A11052779) and Institute for Information and Communications Technology Promotion (IITP) Grant (R0126-16-1078), both funded by the Korea government (MSIP).

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Authors and Affiliations

  1. Department of Computer Science and Engineering, POSTECH, Pohang, Korea

    Junho Jeon, Yeongyu Jung, Haejoon Kim & Seungyong Lee

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  1. Junho Jeon
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  2. Yeongyu Jung
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  3. Haejoon Kim
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  4. Seungyong Lee
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Correspondence to Seungyong Lee.

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Jeon, J., Jung, Y., Kim, H. et al. Texture map generation for 3D reconstructed scenes. Vis Comput 32, 955–965 (2016). https://doi.org/10.1007/s00371-016-1249-5

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