A course representation of frames oriented video coding by leveraging cuboidal partitioning of image data

Ashek Ahmmed; Manoranjan Paul; Manzur Murshed; David Taubman

doi:10.1109/MMSP48831.2020.9287138

A course representation of frames oriented video coding by leveraging cuboidal partitioning of image data

Ashek Ahmmed, Manoranjan Paul, Manzur Murshed, David Taubman

Research output: Book chapter/Published conference paper › Conference paper › peer-review

5 Citations (Scopus)

Abstract

Video coding algorithms attempt to minimize the significant commonality that exists within a video sequence.Each new video coding standard contains tools that can perform this task more efficiently compared to its predecessors. In this work, we form a coarse representation of the current frame by minimizing commonality within that frame while preserving important structural properties of the frame. The building blocks of this coarse representation are rectangular regions called cuboids, which are computationally simple and has a compact description. Then we propose to employ the coarse frame as an additional source for predictive coding of the current frame.Experimental results show an improvement in bit rate savings over a reference codec for HEVC, with minor increase in the codec computational complexity.

Original language	English
Title of host publication	IEEE 22nd International Workshop on Multimedia Signal Processing
Place of Publication	United States
Publisher	IEEE
Pages	1-6
Number of pages	6
ISBN (Electronic)	9781728193205
DOIs	https://doi.org/10.1109/MMSP48831.2020.9287138
Publication status	Published - 2020
Event	IEEE 22nd International Workshop on Multimedia Signal Processing - Virtual workshop Duration: 21 Sept 2020 → 24 Sept 2020 https://attend.ieee.org/mmsp-2020/about/ https://ieeexplore.ieee.org/xpl/conhome/9287028/proceeding (proceedings)

Conference

Conference	IEEE 22nd International Workshop on Multimedia Signal Processing
Period	21/09/20 → 24/09/20
Other	IEEE MMSP 2020 will be held on September 21–24, 2020. The workshop will be organised as a fully virtual event. MMSP 2020 was to be held in the vibrant city of Tampere, Finland. Tampere is known for its active science and business community, nice location on a scenic spot between two great lakes, and world-class services for its citizens and visitors. It is a lively city, which welcomes millions of congress goers every year. Tampere is easily reachable by air, train and car and offers excellent hosting for any budget. We welcome you to visit Tampere when the situation allows it! The workshop is 22nd in the series, organized by the Multimedia Signal Processing Technical Committee of the IEEE Signal Processing Society (SPS), with the aim to bring together researchers and practitioners from academia and industry, passionate about multimedia signal processing, to share their knowledge, exchange ideas, explore future research directions and network.
Internet address	https://attend.ieee.org/mmsp-2020/about/ https://ieeexplore.ieee.org/xpl/conhome/9287028/proceeding (proceedings)

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10.1109/MMSP48831.2020.9287138

Cite this

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title = "A course representation of frames oriented video coding by leveraging cuboidal partitioning of image data",

abstract = "Video coding algorithms attempt to minimize the significant commonality that exists within a video sequence.Each new video coding standard contains tools that can perform this task more efficiently compared to its predecessors. In this work, we form a coarse representation of the current frame by minimizing commonality within that frame while preserving important structural properties of the frame. The building blocks of this coarse representation are rectangular regions called cuboids, which are computationally simple and has a compact description. Then we propose to employ the coarse frame as an additional source for predictive coding of the current frame.Experimental results show an improvement in bit rate savings over a reference codec for HEVC, with minor increase in the codec computational complexity.",

author = "Ashek Ahmmed and Manoranjan Paul and Manzur Murshed and David Taubman",

year = "2020",

doi = "10.1109/MMSP48831.2020.9287138",

language = "English",

pages = "1--6",

booktitle = "IEEE 22nd International Workshop on Multimedia Signal Processing",

publisher = "IEEE",

note = "IEEE 22nd International Workshop on Multimedia Signal Processing ; Conference date: 21-09-2020 Through 24-09-2020",

url = "https://attend.ieee.org/mmsp-2020/about/, https://ieeexplore.ieee.org/xpl/conhome/9287028/proceeding",

}

Ahmmed, A, Paul, M, Murshed, M & Taubman, D 2020, A course representation of frames oriented video coding by leveraging cuboidal partitioning of image data. in IEEE 22nd International Workshop on Multimedia Signal Processing. IEEE, United States, pp. 1-6, IEEE 22nd International Workshop on Multimedia Signal Processing, 21/09/20. https://doi.org/10.1109/MMSP48831.2020.9287138

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AU - Ahmmed, Ashek

AU - Paul, Manoranjan

AU - Murshed, Manzur

AU - Taubman, David

PY - 2020

Y1 - 2020

N2 - Video coding algorithms attempt to minimize the significant commonality that exists within a video sequence.Each new video coding standard contains tools that can perform this task more efficiently compared to its predecessors. In this work, we form a coarse representation of the current frame by minimizing commonality within that frame while preserving important structural properties of the frame. The building blocks of this coarse representation are rectangular regions called cuboids, which are computationally simple and has a compact description. Then we propose to employ the coarse frame as an additional source for predictive coding of the current frame.Experimental results show an improvement in bit rate savings over a reference codec for HEVC, with minor increase in the codec computational complexity.

AB - Video coding algorithms attempt to minimize the significant commonality that exists within a video sequence.Each new video coding standard contains tools that can perform this task more efficiently compared to its predecessors. In this work, we form a coarse representation of the current frame by minimizing commonality within that frame while preserving important structural properties of the frame. The building blocks of this coarse representation are rectangular regions called cuboids, which are computationally simple and has a compact description. Then we propose to employ the coarse frame as an additional source for predictive coding of the current frame.Experimental results show an improvement in bit rate savings over a reference codec for HEVC, with minor increase in the codec computational complexity.

U2 - 10.1109/MMSP48831.2020.9287138

DO - 10.1109/MMSP48831.2020.9287138

M3 - Conference paper

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BT - IEEE 22nd International Workshop on Multimedia Signal Processing

PB - IEEE

CY - United States

T2 - IEEE 22nd International Workshop on Multimedia Signal Processing

Y2 - 21 September 2020 through 24 September 2020

ER -

A course representation of frames oriented video coding by leveraging cuboidal partitioning of image data

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