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      A relevance feedback technique for multimodal retrieval of news videos

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      Author
      Aksoy, Selim
      Çavuş Özge
      Date
      2005-11
      Source Title
      EUROCON 2005 - The International Conference on Computer as a Tool
      Publisher
      IEEE
      Pages
      139 - 142
      Language
      English
      Type
      Conference Paper
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      Abstract
      Content-based retrieval in news video databases has become an important task with the availability of large quantities of data in both public and proprietary archives. We describe a relevance feedback technique that captures the significance of different features at different spatial locations in an image. Spatial content is modeled by partitioning images into non-overlapping grid cells. Contributions of different features at different locations are modeled using weights defined for each feature in each grid cell. These weights are iteratively updated based on user's feedback in terms of positive and negative labeling of retrieval results. Given this labeling, the weight updating scheme uses the ratios of standard deviations of the distances between relevant and irrelevant images to the standard deviations of the distances between relevant images. The proposed technique is quantitatively and qualitatively evaluated using shots related to several sports from the news video collection of the TRECVID video retrieval evaluation where the weights could capture relative contributions of different features and spatial locations. © 2005 IEEE.
      Keywords
      News videos
      Relevance feedback
      Sports videos
      TRECVID
      Video retrieval
      Computer simulation
      Feature extraction
      Feedback control
      Image analysis
      Video signal processing
      Content based retrieval
      Permalink
      http://hdl.handle.net/11693/27365
      Published Version (Please cite this version)
      https://doi.org/10.1109/EURCON.2005.1629878
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      • Department of Computer Engineering 1398
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