Dominant sets clustering for image retrieval

Signal Processing

Volumn 88, Issue 11, 2008, Pages 2843-2849

  Wang, Man ^a   Ye, Zheng Lin ^a   Wang, Yue ^a   Wang, Shu Xun ^a,b  

^a NORTHWESTERN POLYTECHNICAL UNIVERSITY   (China)

^b SHAANXI UNIVERSITY OF TECHNOLOGY   (China)

Author keywords

Content based image retrieval (CBIR); Dominant set clustering (DSC); SVM

Indexed keywords

CONTROL THEORY; DATABASE SYSTEMS; DIFFERENTIAL SCANNING CALORIMETRY; DIGITAL CAMERAS; FEEDBACK; FLOW OF SOLIDS; IMAGE ENHANCEMENT; INFORMATION ANALYSIS; INFORMATION RETRIEVAL; INFORMATION SCIENCE; LASER INTERFEROMETRY; LEARNING SYSTEMS; MILITARY DATA PROCESSING; SUPPORT VECTOR MACHINES;

AVERAGE PRECISION; CONVERGENCE (MATHEMATICS); COREL IMAGE DATABASE; DOMINANT SET; ELSEVIER (CO); FEATURE SIMILARITIES; IMAGE RETRIEVAL SYSTEMS; LEARNING MACHINES; RELEVANCE FEEDBACK (RRF); RETRIEVAL (MIR); RETRIEVAL ALGORITHMS; SUPPORT VECTOR MACHINE (SVM); VISUAL FEATURES;

IMAGE RETRIEVAL;

EID: 47749123443     PISSN: 01651684     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.sigpro.2008.04.007     Document Type: Article

References (13)

1. Smeulders A.W.M., Worring M., Santini S., Gupta A., and Jain R. Content-based image retrieval at the end of the early years. IEEE Trans. Pattern Anal. Mach. Intell. 22 12 (2000 December) 1349-1380
2. Yan C., Sang N., and Zhang T. Survey on graph theory based image segmentation technique. Proc. Comput. Eng. Appl. 42 5 (2006) 11-14
3. M. Pavan, M. Pelillo, A new graph-theoretic approach to clustering and segmentation, in: Proceedings ninth IEEE International Conference on Computer Vision, vol. 1, 2003 October, pp. 145-152.
4. A. Torsello, M. Pavan, M. Pelillo, Spatio-temporal segmentation using dominant sets, in: fifth International Energy Minimization Methods in Computer Vision and Pattern Recognition, St. Augustine, FL, USA, vol. 3757, 2005 November, pp. 301-315 Proceedings.
5. M. Pavan, M. Pelillo, Efficient out-of-sample extension of dominant-set clusters: advances in neural information processing systems 17, in: L.K. Saul, Y. Weiss, L. Bottou (Eds.), 2005, pp. 1057-1064.
6. M. Pavan, M. Pelillo, Efficiently Segmenting Images with Dominant Sets, Rivista Lecture Notes in Computer Science, vol. 3212, pp. 17-24.
7. M. Pavan, M. Pelillo, Unsupervised texture segmentation by dominant sets and game dynamics, in: Proceedings of the 12th International Conference on Image Analysis and Processing, Mantova, Italy, 2003 September, pp. 302-307.
8. M. Pavan, M. Pelillo, Dominant sets and hierarchical clustering, in: Proceedings of the ninth IEEE International Conference on Computer Vision, vol. 1 2003 October, pp. 362-369.
9. Pavan M., and Pelillo M. Dominant sets and pairwise clustering, pattern analysis and machine intelligence. IEEE T. Pattern Anal. 29 1 (2007 January) 167-172
10. Li T., Fu X.P., Li H.Y., et al. A microarray cluster algorithm based on dominant set segmentation. J. Software 16 (2005) 1591-1598
11. Chatterjee M., Das S.K., and Turgut D. A weighted clustering algorithm for mobile ad hoc networks. J. Cluster Comput. Spec. Issue Mobile Ad hoc Networks 5 (2002) 193-204
12. X. Li, W. Hu, W. Hu, A coarse-to-fine strategy for vehicle motion trajectory clustering, in: 18th International Conference on Pattern Recognition, Hong Kong, PRC, vol. 1, 2006 August, pp. 591-594.
13. C.C. Chang, C.J. Lin, SVM-2.84 (April 2007) 〈http://www.csie.ntu.edu.tw/~cjlin/libsvm/〉.