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International Conference on Computational Collective Intelligence

ICCCI 2010: Computational Collective Intelligence. Technologies and Applications pp 75–84Cite as

The Similarity of Video Based on the Association Graph Construction of Video Objects

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6422))

Abstract

We have proposed 9DST approach to represent the spatial-temporal relations between objects in a symbolic video and the similarity of videos is relevant to the users’ requests. In this paper, based on the 9DST approach, we proposed the similarity retrieval algorithm. First, we construct the 9DST index structure, from the 9DST-strings, which contains the spatial-temporal relations for each pair of objects in a video database. Second, we use the similar pairs to define various types of similarity measures and construct the association graph to calculate the similarity between videos. By providing different level types of similarity between videos, our proposed similarity retrieval algorithm has discrimination power about different criteria.

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Author information

Authors and Affiliations

  1. Department of Information Management, Chinese Culture University, Taipei, Taiwan

    Ping Yu

Authors
  1. Ping Yu
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Editor information

Editors and Affiliations

  1. Department of Electronic Engineering, National Kaohsiung University of Applied Sciences, 415 Chien-Kung Road, 807, Kaohsiung, Taiwan

    Jeng-Shyang Pan

  2. Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, #43, Sec.4, Keelung Rd., 106, Taipei, Taiwan

    Shyi-Ming Chen

  3. Institute of Informatics, Wroclaw University of Technology, Str. Wyb. Wyspianskiego 27, 50-370, Wroclaw, Poland

    Ngoc Thanh Nguyen

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© 2010 Springer-Verlag Berlin Heidelberg

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Yu, P. (2010). The Similarity of Video Based on the Association Graph Construction of Video Objects. In: Pan, JS., Chen, SM., Nguyen, N.T. (eds) Computational Collective Intelligence. Technologies and Applications. ICCCI 2010. Lecture Notes in Computer Science(), vol 6422. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16732-4_9

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  • DOI: https://doi.org/10.1007/978-3-642-16732-4_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-16731-7

  • Online ISBN: 978-3-642-16732-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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