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International Symposium on Visual Computing

ISVC 2009: Advances in Visual Computing pp 450–459Cite as

Online Video Textures Generation

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5876))

Abstract

In this paper, we propose two different online approaches for synthesizing video textures. The first approach is through incremental Isomap and Autoregressive (AR) process. It can generate good quality results, nonetheless, it does not extend well for videos that are more sparse, such as cartoons. Our second online video texture generation approach exploits incremental spatio-temporal Isomap (IST-Isomap) and AR process. This second approach can provide more efficient and better quality results for sparse videos than the first approach. Here, the IST-Isomap, which we proposed, is an extension of spatio-temporal Isomap (ST-Isomap) and incremental Isomap. It contains spatio-temporal coherence in the data set and can also be applied in an incremental mode. Compared with other video texture generation approaches, both of our online approaches are able to synthesize new video textures incrementally which in turn offer advantages (e.g. faster and more efficient) in applications where data are sequentially obtained.

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References

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Author information

Authors and Affiliations

  1. Institute for Information Systems Engineering, University of Concordia, Montreal, Canada

    Wentao Fan & Nizar Bouguila

Authors
  1. Wentao Fan
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  2. Nizar Bouguila
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, University of Nevada, Reno, USA

    George Bebis

  2. NASA Ames Research Center, Moffett Field, CA, USA

    Richard Boyle

  3. Lawrence Berkeley National Laboratory, Berkeley, CA, USA

    Bahram Parvin

  4. Desert Research Institute, Reno, NV, USA

    Darko Koracin

  5. Graduate School of Science and Engineering, Saitama University, 255 Shimo-Okubo, Sakura-ku, Saitama-shi, 338-8570, 338-8570, Japan

    Yoshinori Kuno

  6. Microsoft Research, Redmond, WA, USA

    Junxian Wang

  7. Univ. of Zurich, Department of Informatics, Winterthurerstr. 190, P.O. Box, 8057, Zurich, Switzerland

    Renato Pajarola

  8. Lawrence Livermore National Laboratory, 94550, Livermore, CA, USA

    Peter Lindstrom

  9. University of Applied Sciences Bonn-Rhein-Sieg, 53754, Sankt Augustin, Germany

    André Hinkenjann

  10.  ,  

    Miguel L. Encarnação

  11. SCI Institute & School of Computing, University of Utah, 84112, Salt Lake City, UT, USA

    Cláudio T. Silva

  12. Desert Research Institute, 89512, Reno, NV, USA

    Daniel Coming

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© 2009 Springer-Verlag Berlin Heidelberg

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Cite this paper

Fan, W., Bouguila, N. (2009). Online Video Textures Generation. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2009. Lecture Notes in Computer Science, vol 5876. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10520-3_42

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  • DOI: https://doi.org/10.1007/978-3-642-10520-3_42

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-10519-7

  • Online ISBN: 978-3-642-10520-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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