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ABSTRACT
The Carnegie Mellon University Informedia group has enjoyed consistent success with TRECVID interactive search using traditional storyboard interfaces for shot-based retrieval. For TRECVID 2006 the output of automatic search was included for the first time with storyboards, both as an option for an interactive user and in a different run as the sole means of access. The automatic search makes use of relevance-based probabilistic retrieval models to determine weights for combining retrieval sources when addressing a given topic. Storyboard-based access using automatic search output outperformed extreme video retrieval interfaces of manual browsing with resizable pages and rapid serial visualization of keyframes that used the same output. Further, the full Informedia interface with automatic search results as an option along with other query mechanisms scored significantly better than all other TRECVID 2006 interactive search systems. Attributes of the automatic search and interactive search systems are discussed to further optimize shot-based retrieval from news corpora.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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CITED BY 6
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Huanbo Luan , Yantao Zheng , Shi-Yong Neo , Yongdong Zhang , Shouxun Lin , Tat-Seng Chua, Adaptive multiple feedback strategies for interactive video search, Proceedings of the 2008 international conference on Content-based image and video retrieval, July 07-09, 2008, Niagara Falls, Canada
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