APEX - An adaptive Visual Information Retrieval system

被引:0
作者
de Mauro, C [1 ]
Gori, M [1 ]
Maggini, M [1 ]
机构
[1] Univ Siena, Dipartimento Ingn Informaz, I-53100 Siena, Italy
来源
SIXTH INTERNATIONAL CONFERENCE ON DOCUMENT ANALYSIS AND RECOGNITION, PROCEEDINGS | 2001年
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Given a user's visual query, most Visual Information Retrieval (VIR) systems rank the images in the database according to a predefined measure of similarity and return the most similar ones. We propose an adaptive VIR system that uses a retrieval process based on relevance feedback in order to learn the similarity criterion from the user. Our system is based on a structured representation of the image which is then processed by a recursive neural network. The search algorithm refines its response trying to minimize the number of steps required to find the target image.
引用
收藏
页码:898 / 902
页数:3
相关论文
共 6 条
  • [1] An optimized interaction strategy for Bayesian relevance feedback
    Cox, IJ
    Miller, ML
    Minka, TP
    Yianilos, PN
    [J]. 1998 IEEE COMPUTER SOCIETY CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, PROCEEDINGS, 1998, : 553 - 558
  • [2] Hagenbuchner M., 1999, EUR S ART NEUR NETW, P63
  • [3] Local grayvalue invariants for image retrieval
    Schmid, C
    Mohr, R
    [J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 1997, 19 (05) : 530 - 535
  • [4] SMITH JR, 1995, IS T SPIE P, V2670
  • [5] SMITH JR, 1996, P ICASSP
  • [6] SPERDUTI A, 1997, IEEE T NEURAL NETWOR, P8