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Unsupervised Video Shot Segmentation Using Global Color and Texture Information

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Book cover Advances in Visual Computing (ISVC 2008)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5358))

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Abstract

This paper presents an effective algorithm to segment color video into shots for video indexing or retrieval applications. This work adds global texture information to our previous work, which extended the scale-invariant feature transform (SIFT) to color global texture SIFT (CGSIFT). Fibonacci lattice-quantization is used to quantize the image and extract five color features for each region of the image using a symmetrical template. Then, in each region of the image partitioned by the template, the entropy and energy of a co-occurrence matrix are calculated as the texture features. With these global color and texture features, we adopt clustering ensembles to segment video shots. Experimental results show that the additional texture features allow the proposed CGTSIFT algorithm to outperform our previous work, fuzzy-c means, and SOM-based shot detection methods.

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Author information

Authors and Affiliations

  1. Dept. of Electrical and Computer Eng., Brigham Young University, Provo, UT, USA

    Yuchou Chang, Dah-Jye Lee & James Archibald

  2. Dept. of Computer Science, City University of Hong Kong, Kowloon, Hong Kong

    Yi Hong

Authors
  1. Yuchou Chang
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  2. Dah-Jye Lee
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  3. Yi Hong
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  4. James Archibald
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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. Digital Image Research Center, Kingston University, London, UK

    Paolo Remagnino

  6. Mitsubishi Electric Research Laboratories, P.O. Box 02139, Cambridge, MA, USA

    Fatih Porikli

  7. Computer and Information Science and Engineering, University of Florida, P.O. Box, FL 32611-6120, Gainsville, USA

    Jörg Peters

  8. IBM T.J. Watson Research Center, 19 Skyline Drive, NY 10532, Hawthorne, USA

    James Klosowski

  9. 128 Memorial Mall, Stewart B001, IN 47907, West Lafayette, USA

    Laura Arns

  10. Denver Museum of Nature and Space, 2001 Colorade Blvd. Denver,, CO 80205, USA

    Yu Ka Chun

  11. Departmen of Computer Science,, NC State University, Campus Box 8206, NC 27695-8206, Raleigh, USA

    Theresa-Marie Rhyne

  12. Los Alamos National Labs, P.O. Box 1663, NM 87545, Los Alamos, USA

    Laura Monroe

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© 2008 Springer-Verlag Berlin Heidelberg

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Chang, Y., Lee, DJ., Hong, Y., Archibald, J. (2008). Unsupervised Video Shot Segmentation Using Global Color and Texture Information. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2008. Lecture Notes in Computer Science, vol 5358. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89639-5_44

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  • DOI: https://doi.org/10.1007/978-3-540-89639-5_44

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-89638-8

  • Online ISBN: 978-3-540-89639-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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