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Online Image Retrieval System Using Long Term Relevance Feedback
Citation key 1020Goldmann2006
Author Lutz Goldmann and Lars Thiele and Thomas Sikora
Title of Book International Conference on Image and Video Retrieval (CIVR)
Year 2006
DOI 10.1007/11788034_43
Address Tempe, AZ, USA
Month jul
Abstract This paper describes an original system for content based image retrieval. It is based on MPEG-7 descriptors and a novel approach for long term relevance feedback using a Bayesian classifier. Each image is represented by a special model that is adapted over multiple feedback rounds and even multiple sessions or users. The experiments show its outstanding performance in comparison to often used short term relevance feedback and the recently proposed FIRE system.
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