Abstract
Large video collections present a unique set of challenges to the search system designer. Text transcripts do not always provide an accurate index to the visual content, and the performance of visually based semantic extraction techniques is often inadequate for search tasks. The searcher must be relied upon to provide detailed judgment of the relevance of specific video segments. We describe a video search system that facilitates this user task by efficiently presenting search results in semantically meaningful units to simplify exploration of query results and query reformulation. We employ a story segmentation system and supporting user interface elements to effectively present query results at the story level. The system was tested in the 2004 TRECVID interactive search evaluations with very positive results.
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Keywords
- Automatic Speech Recognition
- Latent Semantic Analysis
- Query Term
- Mean Average Precision
- Interactive Video
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Adcock, J., Cooper, M., Girgensohn, A., Wilcox, L. (2005). Interactive Video Search Using Multilevel Indexing. In: Leow, WK., Lew, M.S., Chua, TS., Ma, WY., Chaisorn, L., Bakker, E.M. (eds) Image and Video Retrieval. CIVR 2005. Lecture Notes in Computer Science, vol 3568. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11526346_24
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DOI: https://doi.org/10.1007/11526346_24
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-27858-0
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