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From raw data to semantically enriched hyperlinking: Recent advances in the LinkedTV analysis workflow

: Stein, Daniel; Öktem, Alp; Apostolidis, Evlampios; Mezaris, Vasileios; Redondo García, José Luis; Troncy, Raphaël; Sahuguet, Mathilde; Huet, Benoit

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Torrenti, R. ; European Institute for Research and Strategic Studies in Telecommunications -EURESCOM-, Heidelberg; Networked and Electronic Media -NEM-:
NEM Summit 2013. Conference Proceedings : Implementing Future Media Internet towards New Horizons Maximizing the global value of Content, Media and Networks, Nantes, October 28-30, 2013
Heidelberg: EURESCOM, 2013
ISBN: 978-3-00-043123-4
NEM Summit <2013, Nantes>
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IAIS ()

Enriching linear videos by offering continuative and related information via, e.g., audio streams, web pages, as well as other videos, is typically hampered by its demand for massive editorial work. While a large number of analysis techniques that extract knowledge automatically from video content exists, their produced raw data are typically not of interest to the enduser. In this paper, we review our analysis efforts as defined within the LinkedTV project and present the recent advances in core technologies for automatic speech recognition and object-redetection. Furthermore, we introduce our approach for an automatically generated localized person identification database. Finally, the processing of the raw data into a linked resource available in a web compliant format is described.