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MIR
2010
ACM

Exploiting external knowledge to improve video retrieval

13 years 10 months ago
Exploiting external knowledge to improve video retrieval
Most video retrieval systems are multimodal, commonly relying on textual information, low- and high-level semantic features extracted from query visual examples. In this work, we study the impact of exploiting different knowledge sources in order to automatically retrieve query visual examples relevant to a video retrieval task. Our hypothesis is that the exploitation of external knowledge sources can help on the identification of query semantics as well as on improving the understanding of video contents. We propose a set of techniques to automatically obtain additional query visual examples from different external knowledge sources, such as DBPedia, Flickr and Google Images, which have different coverage and structure characteristics. The proposed strategies attempt to exploit the semantics underlying the above knowledge sources to reduce the ambiguity of the query, and to focus the scope of the image searches in the repositories. We assess and compare the quality of the images obta...
David Vallet, Iván Cantador, Joemon M. Jose
Added 17 May 2010
Updated 17 May 2010
Type Conference
Year 2010
Where MIR
Authors David Vallet, Iván Cantador, Joemon M. Jose
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