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Authors: Rhoda Gbadeyan and Chris Joslin

Affiliation: Department of Systems and Computer Engineering, Carleton University, Ottawa, Canada

Keyword(s): Video Compression, Object-based Coding, Background Subtraction, Object Detection.

Abstract: Standard video compression techniques have provided pixel-based solutions that have achieved high compression performance. However, with new application areas such as streaming, ultra-high definition TV(UHDTV) etc., expectations of end user applications are at an all-time high. Never the less, the issue of stringent memory and bandwidth optimization remains. Therefore, there is a need to further optimize the performance of standard video codecs to provide more flexibility to content providers on how to encode video. In this paper, we propose replacing pixels with objects as the unit of compression while still harnessing the advantages of standard video codecs thereby reducing the bits required to represent a video scene while still achieving suitable visual quality in compressed videos. Test results indicate that the proposed algorithm provides a viable hybrid video coding solution for applications where pixel level precision is not required.

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Paper citation in several formats:
Gbadeyan, R. and Joslin, C. (2021). Object based Hybrid Video Compression. In Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 5: VISAPP; ISBN 978-989-758-488-6; ISSN 2184-4321, SciTePress, pages 785-792. DOI: 10.5220/0010207607850792

@conference{visapp21,
author={Rhoda Gbadeyan. and Chris Joslin.},
title={Object based Hybrid Video Compression},
booktitle={Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 5: VISAPP},
year={2021},
pages={785-792},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010207607850792},
isbn={978-989-758-488-6},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 5: VISAPP
TI - Object based Hybrid Video Compression
SN - 978-989-758-488-6
IS - 2184-4321
AU - Gbadeyan, R.
AU - Joslin, C.
PY - 2021
SP - 785
EP - 792
DO - 10.5220/0010207607850792
PB - SciTePress

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