Publication Type
Journal Article
Version
publishedVersion
Publication Date
8-2006
Abstract
In content-based image retrieval (CBIR), relevant images are identified based on their similarities to query images. Most CBIR algorithms are hindered by the semantic gap between the low-level image features used for computing image similarity and the high-level semantic concepts conveyed in images. One way to reduce the semantic gap is to utilize the log data of users' feedback that has been collected by CBIR systems in history, which is also called “collaborative image retrieval.” In this paper, we present a novel metric learning approach, named “regularized metric learning,” for collaborative image retrieval, which learns a distance metric by exploring the correlation between low-level image features and the log data of users' relevance judgments. Compared to the previous research, a regularization mechanism is used in our algorithm to effectively prevent overfitting. Meanwhile, we formulate the proposed learning algorithm into a semidefinite programming problem, which can be solved very efficiently by existing software packages and is scalable to the size of log data. An extensive set of experiments has been conducted to show that the new algorithm can substantially improve the retrieval accuracy of a baseline CBIR system using Euclidean distance metric, even with a modest amount of log data. The experiment also indicates that the new algorithm is more effective and more efficient than two alternative algorithms, which exploit log data for image retrieval.
Keywords
Content-based image retrieval, Relevance feedback, Log-based relevance feedback, Relevance feedback log, Users, Semantic gap, Metric learning, Regularization, Semidefinite programming
Discipline
Computer Sciences | Databases and Information Systems
Research Areas
Data Science and Engineering
Publication
Multimedia Systems
Volume
12
Issue
1
First Page
34
Last Page
44
ISSN
0942-4962
Identifier
10.1007/s00530-006-0033-1
Publisher
Springer
Citation
SI, Luo; JIN, Rong; HOI, Steven C. H.; and LYU, Michael R..
Collaborative Image Retrieval via Regularized Metric Learning. (2006). Multimedia Systems. 12, (1), 34-44.
Available at: https://ink.library.smu.edu.sg/sis_research/2304
Copyright Owner and License
Publisher
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1007/s00530-006-0033-1