Three Interfaces for Content-Based Access to Image Collections

This paper describes interfaces for a suite of three recently developed techniques to facilitate content-based access to large image and video repositories. Two of these techniques involve content-based retrieval while the third technique is centered around a new browsing structure and forms a useful complement to the traditional query-by-example paradigm. Each technique is associated with its own user interface and allows for a different set of user interactions. The user can move between interfaces whilst executing a particular search and thus may combine the particular strengths of the different techniques. We illustrate each of the techniques using topics from the TRECVID 2003 contest.

[1]  Stefan M. Rüger,et al.  Performance Comparison of Different Similarity Models for CBIR with Relevance Feedback , 2003, CIVR.

[2]  Wei-Ying Ma,et al.  Image and Video Retrieval , 2003, Lecture Notes in Computer Science.

[3]  Duncan J. Watts,et al.  Collective dynamics of ‘small-world’ networks , 1998, Nature.

[4]  Iain Campbell,et al.  The ostensive model of developing information needs , 2000 .

[5]  Daniel Heesch,et al.  Performance boosting with three mouse clicks - Relevance feedback for CBIR , 2003 .

[6]  Simone Santini,et al.  Emergent Semantics through Interaction in Image Databases , 2001, IEEE Trans. Knowl. Data Eng..

[7]  Stefan Rüger,et al.  Networks for Content-Based Image Retrieval , 2004 .

[8]  Sugata Ghosal,et al.  An image retrieval system with automatic query modification , 2002, IEEE Trans. Multim..

[9]  Stefan M. Rüger,et al.  NNk Networks for Content-Based Image Retrieval , 2004, ECIR.

[10]  Ricardo da Silva Torres,et al.  Visual structures for image browsing , 2003, CIKM '03.

[11]  Dragutin Petkovic,et al.  Query by Image and Video Content: The QBIC System , 1995, Computer.

[12]  Qi Tian,et al.  Display Optimization for Image Browsing , 2001, MDIC.

[13]  Anthony P. Lucido Software Systems for Computer Graphics , 1976, Computer.

[14]  Thomas S. Huang,et al.  Relevance feedback: a power tool for interactive content-based image retrieval , 1998, IEEE Trans. Circuits Syst. Video Technol..

[15]  Thierry Pun,et al.  Strategies for positive and negative relevance feedback in image retrieval , 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.