Conference Proceeding

Video Watermarking for Persistent and Robust Tracking of Entertainment Content (PARTEC)

Citation

Bhowmik D, Abhayaratne C & Green S (2021) Video Watermarking for Persistent and Robust Tracking of Entertainment Content (PARTEC). In: Mandal JK, Mukherjee I, Bakshi S, Chatterji S & Sa PK (eds.) Computational Intelligence and Machine Learning. Advances in Intelligent Systems and Computing, 1276. 7th International Conference on Advanced Computing, Networking, and Informatics (ICACNI 2019), West Bengal, India. Singapore: Springer, pp. 185-198. https://doi.org/10.1007/978-981-15-8610-1_19

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.

StatusPublished
FundersInnovate UK
Title of seriesAdvances in Intelligent Systems and Computing
Number in series1276
Publication date31/12/2021
Publication date online25/11/2020
URLhttp://hdl.handle.net/1893/32104
PublisherSpringer
Place of publicationSingapore
ISSN of series2194-5357
ISBN9789811586095
eISBN9789811586101
Conference7th International Conference on Advanced Computing, Networking, and Informatics (ICACNI 2019)
Conference locationWest Bengal, India

Research centres/groups