University of Hertfordshire

By the same authors

Metadata Extraction and Classification of YouTube Videos Using Sentiment Analysis

Research output: Chapter in Book/Report/Conference proceedingConference contribution


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Original languageEnglish
Title of host publicationIEEE International Carnahan Conference on Security Technology
Subtitle of host publicationICCST2016
Place of PublicationUS
PublisherIEEE 978-1-5090
Number of pages7
Publication statusPublished - 24 Oct 2016
EventIEEE International Carnahan Conference on Security Technology - US, Orlando, Florida, United States
Duration: 24 Oct 201627 Oct 2016


ConferenceIEEE International Carnahan Conference on Security Technology
Country/TerritoryUnited States
CityOrlando, Florida


MPEG media have been widely adopted and is very successful in promoting interoperable services that deliver video to consumers on a range of devices. However, media consumption is going beyond the mere playback of a media asset and is geared towards a richer user experience that relies on rich metadata and content description. This paper proposes a technique for extracting and analysing metadata from a video, followed by decision making related to the video content. The system uses sentiment analysis for such a classification. It is envisaged that the system when fully developed, is to be applied to determine the existence of illicit multimedia content on the web.


Soodamani, R & Varsani, V (2016), Vehicle Detection for Traffic Flow Analysis, ICCST2016, Paper presented at the IEEE International Carnahan Conference on Security Technology, 24-27 October 2016, Orlando, Florida.

ID: 10528436