Abstract
In this paper, we present a new multiple regions and their spatial relationship-based image retrieval method. In this method, a semantic object is integrated as a set of related regions based on their spatial relationships and visual features. In contrast to other ROI (Regionof- Interest) or multiple region-based algorithms, we use the Hausdorff Distance (HD) to estimate spatial relationships between regions. By our proposed HD, we can simplify matching process between complex spatial relationships and admit spatial variations of regions, such as translation, rotation, insertion, and deletion. Furthermore, to solve the weight adjust problem automatically and to reflect user’s perceptual subjectivity to the system, we incorporate relevance feedback mechanism into our similarity measure process.
| Original language | English |
|---|---|
| Title of host publication | Image and Video Retrieval - International Conference, CIVR 2002, Proceedings |
| Editors | Michael S. Lew, Nicu Sebe, John P. Eakins |
| Publisher | Springer Verlag |
| Pages | 81-90 |
| Number of pages | 10 |
| ISBN (Electronic) | 9783540438991 |
| Publication status | Published - 2002 Jan 1 |
| Event | International Conference on Image and Video Retrieval, CIVR 2002 - London, United Kingdom Duration: 2002 Jul 18 → 2002 Jul 19 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 2383 |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Other
| Other | International Conference on Image and Video Retrieval, CIVR 2002 |
|---|---|
| Country | United Kingdom |
| City | London |
| Period | 02/7/18 → 02/7/19 |
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All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Computer Science(all)
Cite this
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Multiple regions and their spatial relationship-based image retrieval. / Ko, Byoungchul; Byun, Hyeran.
Image and Video Retrieval - International Conference, CIVR 2002, Proceedings. ed. / Michael S. Lew; Nicu Sebe; John P. Eakins. Springer Verlag, 2002. p. 81-90 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2383).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Multiple regions and their spatial relationship-based image retrieval
AU - Ko, Byoungchul
AU - Byun, Hyeran
PY - 2002/1/1
Y1 - 2002/1/1
N2 - In this paper, we present a new multiple regions and their spatial relationship-based image retrieval method. In this method, a semantic object is integrated as a set of related regions based on their spatial relationships and visual features. In contrast to other ROI (Regionof- Interest) or multiple region-based algorithms, we use the Hausdorff Distance (HD) to estimate spatial relationships between regions. By our proposed HD, we can simplify matching process between complex spatial relationships and admit spatial variations of regions, such as translation, rotation, insertion, and deletion. Furthermore, to solve the weight adjust problem automatically and to reflect user’s perceptual subjectivity to the system, we incorporate relevance feedback mechanism into our similarity measure process.
AB - In this paper, we present a new multiple regions and their spatial relationship-based image retrieval method. In this method, a semantic object is integrated as a set of related regions based on their spatial relationships and visual features. In contrast to other ROI (Regionof- Interest) or multiple region-based algorithms, we use the Hausdorff Distance (HD) to estimate spatial relationships between regions. By our proposed HD, we can simplify matching process between complex spatial relationships and admit spatial variations of regions, such as translation, rotation, insertion, and deletion. Furthermore, to solve the weight adjust problem automatically and to reflect user’s perceptual subjectivity to the system, we incorporate relevance feedback mechanism into our similarity measure process.
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UR - http://www.scopus.com/inward/citedby.url?scp=77954468441&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:77954468441
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 81
EP - 90
BT - Image and Video Retrieval - International Conference, CIVR 2002, Proceedings
A2 - Lew, Michael S.
A2 - Sebe, Nicu
A2 - Eakins, John P.
PB - Springer Verlag
ER -