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Published in:
2009 | OriginalPaper | Chapter
Improving Automatic Video Retrieval with Semantic Concept Detection
Authors : Markus Koskela, Mats Sjöberg, Jorma Laaksonen
Published in: Image Analysis
Publisher: Springer Berlin Heidelberg
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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.