| Autor: |
Joe Mitchell, Pierre Houdyer, Zbigniew Zdziarski, Rozenn Dahyot, Cyril Bourges, Dave Johnson |
| Rok vydání: |
2014 |
| Předmět: |
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| Zdroj: |
2014 International Workshop on Computational Intelligence for Multimedia Understanding (IWCIM). |
| DOI: |
10.1109/iwcim.2014.7008797 |
| Popis: |
The amount of media that is being uploaded to social sites (such as Twitter, Facebook and Instagram) is providing a wealth of visual data (images and videos) augmented with additional information such as keywords, timestamps and GPS coordinates. Tapastreet1 provides access in real-time to this visual content by harvesting social networks for visual media associated with particular locations, time and hashtags [1]. Browsing efficiently through harvested videos requires smart processing to give users a quick overview of their content in particular when using mobile platforms with limited bandwidth. This paper aims at presenting an architecture for testing several strategies for processing summaries of videos collected on social networks to tackle this issue. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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