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Semantic Retrieval in a Large-Scale Video Database by Using Both Image and Text Feature

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3332))

Abstract

The paper demonstrates a new retrieval method of intergrating both image features and text informations derived from video data. We compare not only image similiarity, also narrow the retrieval sets in advance by employing searching in text keywords. Users inputs also performs the key role in improving retrieval accuracy.

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© 2004 Springer-Verlag Berlin Heidelberg

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Yu, C., Mo, H., Katayama, N., Satoh, S., Asano, S. (2004). Semantic Retrieval in a Large-Scale Video Database by Using Both Image and Text Feature. In: Aizawa, K., Nakamura, Y., Satoh, S. (eds) Advances in Multimedia Information Processing - PCM 2004. PCM 2004. Lecture Notes in Computer Science, vol 3332. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30542-2_95

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  • DOI: https://doi.org/10.1007/978-3-540-30542-2_95

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23977-2

  • Online ISBN: 978-3-540-30542-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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