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SCIA
2009
Springer

Improving Automatic Video Retrieval with Semantic Concept Detection

9 years 8 months ago
Improving Automatic Video Retrieval with Semantic Concept Detection
We study the usefulness of intermediate semantic concepts in bridging the semantic gap in automatic video retrieval. The results of a series of large-scale retrieval experiments, which combine text-based search, content-based retrieval, and concept-based retrieval, is presented. The experiments use the common video data and sets of queries from three successive TRECVID evaluations. By including concept detectors, we observe a consistent improvement on the search performance, despite the fact that the performance of the individual detectors is still often quite modest.
Markus Koskela, Mats Sjöberg, Jorma Laaksonen
Added 27 May 2010
Updated 27 May 2010
Type Conference
Year 2009
Where SCIA
Authors Markus Koskela, Mats Sjöberg, Jorma Laaksonen
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