Benchmarking for Content-Based Visual Information Search

The importance of the visual information search problem has given rise to a large number of systems and prototypes being built to perform such search. While different systems clearly have their particular strengths, they tend to use different collections to highlight the advantages of their algorithms. Consequently, a degree of bias may exist, and it also makes it difficult to make comparisons concerning the relative superiority of different algorithms. In order for the field of visual information search to make further progress, a need therefore exists for a standardised benchmark suite to be developed. By having a uniform measure of search performance, research progress can be more easily recognised and charted, and the resultant synergy will be essential to further development of the field. This paper presents concrete proposals concerning the development of such a benchmark, and by adopting an extensible framework, it is able to cater for a wide variety of applications paradigms and to lend itself to incremental refinement.

[1]  Gerald Salton,et al.  Automatic text processing , 1988 .

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

[3]  Clement H. C. Leung,et al.  Image data modeling for efficient content indexing , 1995, Proceedings. International Workshop on Multi-Media Database Management Systems.

[4]  Shih-Fu Chang,et al.  Visual information retrieval from large distributed online repositories , 1997, CACM.

[5]  George Lawton Storage Technology Takes Center Sstage , 1999, Computer.

[6]  Li Yang,et al.  Towards a Semantic Image Database System , 1997, Data Knowl. Eng..

[7]  Shih-Fu Chang,et al.  Visually Searching the Web for Content , 1997, IEEE Multim..

[8]  Esther Dyson,et al.  Education and jobs in the digital world , 1997, CACM.

[9]  Amarnath Gupta,et al.  Visual information retrieval , 1997, CACM.

[10]  Simone Santini,et al.  In search of information in visual media , 1997, CACM.

[11]  Alberto Del Bimbo,et al.  Using 3D spatial relationships for image retrieval by contents , 1992, Proceedings IEEE Workshop on Visual Languages.

[12]  Fang Wei,et al.  An abstract layered model for hypermedia document system , 1999, Proceedings IEEE International Conference on Multimedia Computing and Systems.

[13]  Vijay V. Raghavan,et al.  Modeling and retrieving images by content , 1997, Inf. Process. Manag..

[14]  U. Gargi,et al.  Image database querying using a multi-scale localized color representation , 1999, Proceedings IEEE Workshop on Content-Based Access of Image and Video Libraries (CBAIVL'99).

[15]  William I. Grosky,et al.  Managing multimedia information in database systems , 1997, CACM.

[16]  Clement H. C. Leung,et al.  Architecture of a pictorial database management system , 1991 .

[17]  K. Selçuk Candan,et al.  Hierarchical Image Modeling for Object-Based Media Retrieval , 1998, Data Knowl. Eng..

[18]  Clement H. C. Leung Visual Information Systems , 1997, Lecture Notes in Computer Science.

[19]  Michael Stonebraker,et al.  A measure of transaction processing power , 1985 .

[20]  Alberto Del Bimbo,et al.  Semantics in Visual Information Retrieval , 1999, IEEE Multim..

[21]  Z. J. Zheng,et al.  Analysis and Evaluation of Search Efficiency for Image Databases , 1998, Image Databases and Multi-Media Search.

[22]  Horace H. S. Ip,et al.  An open framework for a multimedia medical document system , 1995 .