Abstract
We have been developing new relevance feedback algorithms for Content-based Image Retrieval (CBIR) that allow the user to achieve more flexible query. In conjunction with the new user interface, called group-oriented user interface, the user's interest can be expressed with multiple groups of positive and negative image examples. This provides users with greater flexibility as compared with previous systems that consider image query as one or two-class problems. In this paper, we analyze our new algorithm qualitatively and quantitatively. For comparison with previous approaches, the systems are tested on both toy problems and real image retrieval tasks. From the results of our experiments, we suggest when and how our algorithm has advantages over the previous methods.
| Original language | English (US) |
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| Pages | 599-602 |
| Number of pages | 4 |
| State | Published - 2003 |
| Event | Proceedings: 2003 International Conference on Image Processing, ICIP-2003 - Barcelona, Spain Duration: Sep 14 2003 → Sep 17 2003 |
Other
| Other | Proceedings: 2003 International Conference on Image Processing, ICIP-2003 |
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| Country/Territory | Spain |
| City | Barcelona |
| Period | 9/14/03 → 9/17/03 |
ASJC Scopus subject areas
- Hardware and Architecture
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering