CONTENT-FREE IMAGE RETRIEVAL BASED ON RELATIONS EXPLOITED FROM USER FEEDBACKS (ThuPmOR2)

Author(s) : Shingo Uchihashi (Carnegie Mellon University, United States of America) Takeo Kanade (Carnegie Mellon University, United States of America)

Abstract : We propose a new "content-free" image retrieval method which attempts to exploit certain common tendencies that exist among people's interpretation of images from user feedbacks. The system simply accumulates records of user feedback and recycles them in the form of collaborative filtering. We discuss various issues of image retrieval, argue for the idea of content-free, and present results of preliminary experiment. The results indicate that the performance of content-free image retrieval improves with the number of accumulated feedbacks, outperforming a basic but typical conventional content-based image retrieval system.

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