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Constrained Inter Prediction: Removing Dependencies Between Different Data Partitions

  • Conference paper
Advanced Concepts for Intelligent Vision Systems (ACIVS 2007)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 4678))

Abstract

With the growing demand for low delay video streaming in error-prone environments, error resilience tools, such as the data partitioning tool in the H.264/AVC specification, are becoming more and more important. In this paper, the introduction of constrained inter prediction into the H.264/AVC specification is proposed. Constrained inter prediction can help the data partitioning tool by removing the dependencies between partitions B and C, thereby making it possible to process partition C if partition B is lost. From the experimental results it is observed that the cost for introducing this technique can be neglected. Furthermore, when constrained inter prediction is used in combination with constrained intra prediction, resulting bitstreams have an increased peak signal-to-noise ratio of up to 1.8 dB in error-prone environments compared to when only constrained intra prediction is used.

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Authors and Affiliations

  1. Department of Electronics and Information Systems – Multimedia Lab, Ghent University – IBBT, Gaston Crommenlaan 8 bus 201, B-9050 Ledeberg-Ghent, Belgium

    Yves Dhondt, Stefaan Mys, Kenneth Vermeirsch & Rik Van de Walle

Authors
  1. Yves Dhondt
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  2. Stefaan Mys
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  3. Kenneth Vermeirsch
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  4. Rik Van de Walle
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Editor information

Jacques Blanc-Talon Wilfried Philips Dan Popescu Paul Scheunders

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© 2007 Springer-Verlag Berlin Heidelberg

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Dhondt, Y., Mys, S., Vermeirsch, K., Van de Walle, R. (2007). Constrained Inter Prediction: Removing Dependencies Between Different Data Partitions. In: Blanc-Talon, J., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2007. Lecture Notes in Computer Science, vol 4678. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74607-2_65

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  • DOI: https://doi.org/10.1007/978-3-540-74607-2_65

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-74606-5

  • Online ISBN: 978-3-540-74607-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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