Paper
16 January 2006 Requirements for benchmarking personal image retrieval systems
Jean-Yves Bouguet, Carole Dulong, Igor Kozintsev, Yi Wu
Author Affiliations +
Proceedings Volume 6061, Internet Imaging VII; 606101 (2006) https://doi.org/10.1117/12.660254
Event: Electronic Imaging 2006, 2006, San Jose, California, United States
Abstract
It is now common to have accumulated tens of thousands of personal ictures. Efficient access to that many pictures can only be done with a robust image retrieval system. This application is of high interest to Intel processor architects. It is highly compute intensive, and could motivate end users to upgrade their personal computers to the next generations of processors. A key question is how to assess the robustness of a personal image retrieval system. Personal image databases are very different from digital libraries that have been used by many Content Based Image Retrieval Systems.1 For example a personal image database has a lot of pictures of people, but a small set of different people typically family, relatives, and friends. Pictures are taken in a limited set of places like home, work, school, and vacation destination. The most frequent queries are searched for people, and for places. These attributes, and many others affect how a personal image retrieval system should be benchmarked, and benchmarks need to be different from existing ones based on art images, or medical images for examples. The attributes of the data set do not change the list of components needed for the benchmarking of such systems as specified in2: - data sets - query tasks - ground truth - evaluation measures - benchmarking events. This paper proposed a way to build these components to be representative of personal image databases, and of the corresponding usage models.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jean-Yves Bouguet, Carole Dulong, Igor Kozintsev, and Yi Wu "Requirements for benchmarking personal image retrieval systems", Proc. SPIE 6061, Internet Imaging VII, 606101 (16 January 2006); https://doi.org/10.1117/12.660254
Lens.org Logo
CITATIONS
Cited by 4 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Databases

Image retrieval

Computing systems

Image processing

Performance modeling

Feature extraction

Data modeling

Back to Top