基于反馈日志分析的图像检索相关反馈方法  

A Relevance Feedback Method in Image Retrieval with Analyzing Feedback Log

作　　者：周向东[1] 张亮[1] 张琪[1] 刘莉[1] 施伯乐[1] 

机构地区：[1]复旦大学计算机与信息技术系,上海200433

出　　处：《计算机研究与发展》2004年第1期111-117,共7页Journal of Computer Research and Development

基　　金：国家自然科学基金重点项目 ( 6993 3 919);国家"八六三"高技术研究发展计划基金项目 ( 2 0 0 2AA4Z3 43 0 )

摘　　要：基于内容的图像检索是多媒体数据库研究的重要内容之一 近年来 ,采用用户相关反馈方法提高检索效率的研究已成为新的热点 用户相关反馈是一种交互式的渐进过程 ,如何提高反馈效率 ,减少交互次数是该技术面临的主要问题 提出一种通过对相关反馈历史数据进行在线分析从而加快反馈过程的新方法 对 10 0 0 0幅图像数据库的实验表明 ,与传统相关反馈技术相比 。Content-based image retrieval is one of the most important research areas in multimedia database. In recent years it has been more and more popular to use the mechanism of relevance feedback to improve retrieval performance. However, due to the interactive and iterative characteristics of the relevance feedback, the efficiency is still the main obstacle of the application of this technology in practice. To address this problem a novel approach is presented, which accelerates feedback process by analyzing feedback log file using collaborative filtering model. Through analyzing the log file, the system may get some correlation information to predicate the images' semantic similarity with respect to the current retrieval. A prototype image retrieval system is implemented, and the experiment result show that compared with the traditional relevance feedback method, the retrieval performance can be improved apparently.

关 键 词：基于内容的图像检索 用户相关反馈 协同过滤模型 多媒体数据库 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]