Bhowmik, D., Abhayaratne, C. orcid.org/0000-0002-2799-7395 and Green, S. (2020) Video watermarking for persistent and robust tracking of entertainment content (PARTEC). In: Mandal, J.K., Mukherjee, I., Bakshi, S., Chatterji, S. and Sa, P.K., (eds.) Computational Intelligence and Machine Learning : Proceedings of the 7th International Conference on Advanced Computing, Networking, and Informatics (ICACNI 2019). 7th International Conference on Advanced Computing, Networking, and Informatics (ICACNI 2019), 20-21 Dec 2019, West Bengal, India. Springer Singapore , pp. 185-198. ISBN 9789811586095
Abstract
The exploitation of film and video content on physical media, broadcast and Internet involves working with many large media files. The move to file-based workflows necessitates the copying and transfer of digital assets amongst many parties, but the detachment of assets and their metadata leads to issues of reliability, quality and security. This paper proposes a novel watermarking-based approach to deliver a unique solution to enable digital media assets to be maintained with their metadata persistently and robustly. Watermarking-based solution for entertainment content manifests new challenges, including maintaining high quality of the media content, robustness to compression and file format changes and synchronisation against scene editing. The proposed work addresses these challenges and demonstrates interoperability with an existing industrial software framework for media asset management (MAM) systems.
Metadata
Item Type: | Proceedings Paper |
---|---|
Authors/Creators: |
|
Editors: |
|
Copyright, Publisher and Additional Information: | © 2021 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. This is an author-produced version of a paper subsequently published in Proceedings of the 7th International Conference on Advanced Computing, Networking, and Informatics (ICACNI 2019). Uploaded in accordance with the publisher's self-archiving policy. |
Dates: |
|
Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Electronic and Electrical Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 06 Jan 2021 08:46 |
Last Modified: | 25 Nov 2021 01:38 |
Status: | Published |
Publisher: | Springer Singapore |
Refereed: | Yes |
Identification Number: | 10.1007/978-981-15-8610-1_19 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:169412 |