caa a22 4500 463251393 CHVBK 20180405153341.0 cr unu---uuuuu 170326e20071001xx s 000 0 eng 10.1007/s10791-007-9031-y doi (NATIONALLICENCE)springer-10.1007/s10791-007-9031-y A review of text and image retrieval approaches for broadcast news video [Elektronische Daten] [Rong Yan, Alexander Hauptmann] The effectiveness of a video retrieval system largely depends on the choice of underlying text and image retrieval components. The unique properties of video collections (e.g., multiple sources, noisy features and temporal relations) suggest we examine the performance of these retrieval methods in such a multimodal environment, and identify the relative importance of the underlying retrieval components. In this paper, we review a variety of text/image retrieval approaches as well as their individual components in the context of broadcast news video. Numerous components of text/image retrieval have been discussed in detail, including retrieval models, text sources, temporal expansion methods, query expansion methods, image features, and similarity measures. For each component, we conduct a series of retrieval experiments on TRECVID video collections to identify their advantages and disadvantages. To provide a more complete coverage of video retrieval, we briefly discuss an emerging approach called concept-based video retrieval, and review strategies for combining multiple retrieval outputs. Springer Science+Business Media, LLC, 2007 Video retrieval nationallicence Text retrieval nationallicence Image retrieval nationallicence Concept-based retrieval nationallicence Fusion nationallicence Review nationallicence Yan Rong Intelligent Information Management Department, IBM TJ Watson Research, 19 Skyline Drive, 10532, Hawthorne, NY, USA aut Hauptmann Alexander Language Technologies Institute, Carnegie Mellon University, 15213, Pittsburgh, PA, USA aut Information Retrieval Springer Netherlands 10/4-5(2007-10-01), 445-484 1386-4564 10:4-5<445 2007 10 10791 https://doi.org/10.1007/s10791-007-9031-y text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s10791-007-9031-y text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Yan Rong Intelligent Information Management Department, IBM TJ Watson Research, 19 Skyline Drive, 10532, Hawthorne, NY, USA aut NATIONALLICENCE 700 1- Hauptmann Alexander Language Technologies Institute, Carnegie Mellon University, 15213, Pittsburgh, PA, USA aut NATIONALLICENCE 773 0- Information Retrieval Springer Netherlands 10/4-5(2007-10-01), 445-484 1386-4564 10:4-5<445 2007 10 10791 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer