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Spatio-Temporal Video Segmentation

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Advances in Spatio-Temporal Segmentation of Visual Data

Part of the book series: Studies in Computational Intelligence ((SCI,volume 876))

Abstract

This Chapter considers approaches to video skimming into semantically-consistent segments of video streams, which are highly redundant and weakly structured data. In such a way, one of the promising ways is spatial-temporal segmentation as frame partitions represent certain spatial image content. Also, properties were formulated and proved which ultimately determine the characteristics of permissible segmentation transformations when searching for a compromise between over and undo segmentation. Temporal segmentation of multidimensional time series has been examined, which enables structuring video streams and significantly reduce the amount of data that will require online processing. For this, multidimensional time series analysis theory was used, since a completely natural video representation is a sequence of frames, followed by their combination into groups of frames (shots) with the same content. It was shown that various approaches can be used to detect shots with homogeneous characteristics, which are based on VAR models, exponential smoothing and predictive models.

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Author information

Authors and Affiliations

  1. Kharkiv National University of Radio Electronics, 14 Nauky Ave, Kharkiv, 61166, Ukraine

    Sergii Mashtalir & Volodymyr Mashtalir

Authors
  1. Sergii Mashtalir
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  2. Volodymyr Mashtalir
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Correspondence to Volodymyr Mashtalir .

Editor information

Editors and Affiliations

  1. Kharkiv National University of Radio Electronics, Kharkiv, Ukraine

    Vladimir Mashtalir

  2. Kharkiv National University of Radio Electronics, Kharkiv, Ukraine

    Igor Ruban

  3. Faculty of Management Science and Informatics, University of Žilina, Žilina, Slovakia

    Vitaly Levashenko

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Mashtalir, S., Mashtalir, V. (2020). Spatio-Temporal Video Segmentation. In: Mashtalir, V., Ruban, I., Levashenko, V. (eds) Advances in Spatio-Temporal Segmentation of Visual Data. Studies in Computational Intelligence, vol 876. Springer, Cham. https://doi.org/10.1007/978-3-030-35480-0_4

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  • DOI: https://doi.org/10.1007/978-3-030-35480-0_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-35479-4

  • Online ISBN: 978-3-030-35480-0

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