Name
Title | ||
|---|---|---|
A latent semantic indexing based method for solving multiple instance learning problem in region-based image retrieval |
Abstract | ||
|---|---|---|
Relevance feedback (RF) is a widely used technique in incorporating user's knowledge with the learning process for content-based image retrieval (CBIR). As a supervised learning technique, it has been shown to significantly increase the retrieval accuracy. However, as a CBIR system continues to receive user queries and user feedbacks, the information of user preferences across query sessions are often lost at the end of search, thus requiring the feedback process to be restarted for each new query. A few works targeting long-term learning have been done in general CBIR domain to alleviate this problem. However, none of them address the needs and long-term similarity learning techniques for region-based image retrieval. This paper proposes a latent semantic indexing (LSI) based method to utilize users' relevance feedback information. The proposed region-based image retrieval system is constructed on a multiple instance learning (MIL) framework with one-class support vector machine (SVM) as its core. Experiments show that the proposed method can better utilize users' feedbacks of previous sessions, thus improving the performance of the learning algorithm (one-class SVM). |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1109/ISM.2005.10 | ISM |
Keywords | Field | DocType |
general cbir domain,user feedbacks,latent semantic indexing,retrieval accuracy,proposed regionbased image retrieval,learning (artificial intelligence),user query,regionbased image retrieval,support vector machine,image retrieval,user preference,relevance feedback,multiple instance learning,cbir system,region-based image,long-term learning,region-based image retrieval,multiple instance learning problem,support vector machines,learning algorithm,supervised learning technique,learning artificial intelligence,supervised learning | Similarity learning,Latent semantic indexing,Relevance feedback,Information retrieval,Pattern recognition,Active learning (machine learning),Computer science,Support vector machine,Image retrieval,Supervised learning,Artificial intelligence,Machine learning | Conference |
ISBN | Citations | PageRank |
0-7695-2489-3 | 15 | 0.53 |
References | Authors | |
12 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xin Chen | 1 | 98 | 9.56 |
| Chengcui Zhang | 2 | 789 | 84.56 |
| Shu-Ching Chen | 3 | 1978 | 182.74 |
| Min Chen | 4 | 244 | 14.75 |