Large Scale Image Clustering with Support Vector Machine based on Visual Keywords
Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45) › 32_Refereed conference paper (with ISBN/ISSN)
Author(s)
Related Research Unit(s)
Detail(s)
| Original language | English |
|---|---|
| Title of host publication | MDMKDD '10 - Proceedings of the Tenth International Workshop on Multimedia Data Mining |
| Publication status | Published - 25 Jul 2010 |
Workshop
| Title | 10th International Workshop on Multimedia Data Mining (MDMKDD '10) |
|---|---|
| Place | United States |
| City | Washington |
| Period | 25 July 2010 |
Link(s)
Abstract
Support Vector Machine Clustering (SVMC) is a model-based clustering method designed primarily for solving 2-class clustering problems. In this paper, we generalize the SVMC method to multi-class clustering via two different strategies, namely One-Against-All and hierarchical clustering. We applied the resulting multi-class SVMC techniques to large scale image clustering based on the visual keywords representation and Histogram Intersection Kernel. Experiments on two benchmark databases show that compared with traditional Support Vector Clustering (SVC) method, our proposed approach is particularly suited to large scale data and large number of classes clustering problems, in terms of computational efficiency and clustering quality.
Research Area(s)
- Clustering, Hierarchical, Histogram Intersection Kernel, Image clustering, Multi-class, One-Against-All, Support Vector Machine, Visual keywords
Citation Format(s)
Large Scale Image Clustering with Support Vector Machine based on Visual Keywords. / Chang, Tian-Tian; Ip, Horace H.S.; Feng, Jun.
MDMKDD '10 - Proceedings of the Tenth International Workshop on Multimedia Data Mining. 2010. 5.Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45) › 32_Refereed conference paper (with ISBN/ISSN)
