Share Email Print

Proceedings Paper

On benchmarking content-based image retrieval applications
Author(s): Yuanyuan Zuo; Jinhui Yuan; Dayong Ding; Dong Wang; Bo Zhang
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Constructing a benchmark for content-based image retrieval (CBIR) applications is an important task because researchers in this area highly depend on experiments to compare different systems. Image collection, concept annotation and performance evaluation are the three main issues that should be considered carefully. Based on our previous work and experiments on both Corel image collection and TRECVID dataset, we present some basic principles of constructing a benchmark for CBIR applications. According to our experience in the collaborative annotation of TRECVID 2005 data, we propose a hierarchical concept annotation strategy to produce ground truth for the CBIR benchmark image collection. To address the conflicts among collaborative annotations from multiple annotators, we present a fuzzy annotation method, in which a membership function is defined to indicate the probability that an image contains a given concept. Evaluation criteria corresponding to the fuzzy annotation method are also presented so as to give a more reasonable evaluation of performance for different CBIR applications.

Paper Details

Date Published: 16 January 2006
PDF: 9 pages
Proc. SPIE 6061, Internet Imaging VII, 606106 (16 January 2006); doi: 10.1117/12.660260
Show Author Affiliations
Yuanyuan Zuo, Tsinghua Univ. (China)
Jinhui Yuan, Tsinghua Univ. (China)
Dayong Ding, Tsinghua Univ. (China)
Dong Wang, Tsinghua Univ. (China)
Bo Zhang, Tsinghua Univ. (China)

Published in SPIE Proceedings Vol. 6061:
Internet Imaging VII
Simone Santini; Raimondo Schettini; Theo Gevers, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?