| Autor: |
Schmiedeke, Sebastian, Xu, Peng, Ferrané, Isabelle, Eskevich, Maria, Kofler, Christoph, Larson, Martha A., Estève, Yannick, Lamel, Lori, Jones, Gareth J.F., Sikora, Thomas |
| Přispěvatelé: |
Centre National de la Recherche Scientifique - CNRS (FRANCE), Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE), Technische Universität Berlin - TU Berlin (GERMANY), Université Toulouse III - Paul Sabatier - UT3 (FRANCE), Université Toulouse - Jean Jaurès - UT2J (FRANCE), Université Toulouse 1 Capitole - UT1 (FRANCE), Delft University of Technology - TU Delft (NETHERLANDS), Université du Maine (FRANCE), University of Dublin (REPUBLIC OF IRELAND), Université Paris-Sud 11 (FRANCE), Vocapia Research (FRANCE), Institut de Recherche en Informatique de Toulouse - IRIT (Toulouse, France), Laboratoire d'Informatique de l'Université du Maine (LIUM, Le Mans) |
| Jazyk: |
angličtina |
| Rok vydání: |
2013 |
| Předmět: |
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| Popis: |
The increasing amount of digital multimedia content available is inspiring potential new types of user interaction with video data. Users want to easily find the content by searching and browsing. For this reason, techniques are needed that allow automatic categorisation, searching the content and linking to related information. In this work, we present a dataset that contains comprehensive semi-professional usergenerated (SPUG) content, including audiovisual content,user-contributed metadata, automatic speech recognition transcripts, automatic shot boundary files, and social information for multiple ‘social levels’. We describe the principal characteristics of this dataset and present results that have been achieved on different tasks. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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