Improving Automatic Video Retrieval with Semantic Concept Detection

Authors:
Markus Koskela;Mats Sjöberg;Jorma Laaksonen
Affiliations:
Department of Information and Computer Science, Helsinki University of Technology (TKK), Espoo, Finland;Department of Information and Computer Science, Helsinki University of Technology (TKK), Espoo, Finland;Department of Information and Computer Science, Helsinki University of Technology (TKK), Espoo, Finland
Venue:
SCIA '09 Proceedings of the 16th Scandinavian Conference on Image Analysis
Year:
2009

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Abstract

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.