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A Relevance Feedback Technique for Multimodal Retrieval of News Videos
 

Summary: A Relevance Feedback Technique for
Multimodal Retrieval of News Videos
Selim Aksoy, Member, IEEE and ¨Ozge C¸ avus¸
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

  

Source: Aksoy, Selim - Department of Computer Engineering, Bilkent University

 

Collections: Computer Technologies and Information Sciences