Occam's razor: supporting visual query expression for content-based image queries

This paper reports the results of a usability experiment that investigated visual query formulation on three dimensions: effectiveness, efficiency, and user satisfaction. Twenty eight evaluation sessions were conducted in order to assess the extent to which query by visual example supports visual query formulation in a content-based image retrieval environment. In order to provide a context and focus for the investigation, the study was segmented by image type, user group, and use function. The image type consisted of a set of abstract geometric device marks supplied by the UK Trademark Registry. Users were selected from the 14 UK Patent Information Network offices. The use function was limited to the retrieval of images by shape similarity. Two client interfaces were developed for comparison purposes: Trademark Image Browser Engine (TRIBE) and Shape Query Image Retrieval Systems Engine (SQUIRE).

[1]  Vincenzo Di Lecce,et al.  An Evaluation of the Effectiveness of Image Features for Image Retrieval , 1999, J. Vis. Commun. Image Represent..

[2]  John P. Eakins,et al.  Towards intelligent image retrieval , 2002, Pattern Recognit..

[3]  Eugenio Di Sciascio,et al.  Query by Sketch and Relevance Feedback for Content-Based Image Retrieval over the Web , 1999, J. Vis. Lang. Comput..

[4]  T. D. Wilson,et al.  On user studies and information needs , 2006, J. Documentation.

[5]  Erkki Oja,et al.  PicSOM - content-based image retrieval with self-organizing maps , 2000, Pattern Recognit. Lett..

[6]  Toshikazu Kato,et al.  Multimedia interaction with image database systems , 1990, SGCH.

[7]  G. Rigoll,et al.  Image database retrieval of rotated objects by user sketch , 1998, Proceedings. IEEE Workshop on Content-Based Access of Image and Video Libraries (Cat. No.98EX173).

[8]  Shi-Kuo Chang,et al.  Image Information Systems: Where Do We Go From Here? , 1992, IEEE Trans. Knowl. Data Eng..

[9]  Pamela Briggs,et al.  Image Retrieval Interfaces: A User Perspective , 2004, CIVR.

[10]  Pietro Pala,et al.  Querying by Photographs: A VR Metaphor for Image Retrieval , 2000, IEEE Multim..

[11]  Gary Marchionini,et al.  Information Seeking in Electronic Environments , 1995 .

[12]  Marcel Worring,et al.  Filter Image Browsing: Interactive Image Retrieval by Using Database Overviews , 2001, Multimedia Tools and Applications.

[13]  Fuhui Long,et al.  Fundamentals of Content-Based Image Retrieval , 2003 .

[14]  Karen M. Drabenstott,et al.  Browse and Search Patterns in a Digital Image Database , 2004, Information Retrieval.

[15]  John Tait,et al.  Search strategies in content-based image retrieval , 2003, SIGIR.

[16]  S. Batley Visual information retrieval : browsing strategies in pictorial databases , 1988 .

[17]  Thomas S. Huang,et al.  Extending image retrieval with group-oriented interface , 2002, Proceedings. IEEE International Conference on Multimedia and Expo.

[18]  Simone Santini,et al.  Image Databases Are Not Databases with Images , 1997, ICIAP.

[19]  Naphtali Rishe,et al.  Content-based image retrieval , 1995, Multimedia Tools and Applications.

[20]  S. Sitharama Iyengar,et al.  Content based image retrieval systems , 1999, Proceedings 1999 IEEE Symposium on Application-Specific Systems and Software Engineering and Technology. ASSET'99 (Cat. No.PR00122).

[21]  Kent L. Norman,et al.  Development of an instrument measuring user satisfaction of the human-computer interface , 1988, CHI '88.

[22]  Joemon M. Jose,et al.  Spatial querying for image retrieval: a user-oriented evaluation , 1998, SIGIR '98.

[23]  Shih-Fu Chang,et al.  Concepts and Techniques for Indexing Visual Semantics , 2002 .

[24]  John P. Eakins,et al.  ARTISAN: a shape retrieval system based on boundary family indexing , 1996, Electronic Imaging.

[25]  Thomas S. Huang,et al.  Visual Information Retrieval: Paradigms, Applications, and Research Issues , 2001, Principles of Visual Information Retrieval.

[26]  Marcel Worring,et al.  Content-Based Image Retrieval at the End of the Early Years , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[27]  Christopher C. Yang Content-Based Image Retrieval: A Comparison between Query by Example and Image Browsing Map Approaches , 2004, J. Inf. Sci..

[28]  H. K. Ramapriyan Satellite Imagery in Earth Science Applications , 2002 .