A voting approach to learn affinity matrix for robust clustering

Proceedings - International Conference on Image Processing, ICIP

Volumn , Issue , 2009, Pages 2409-2412

  Parag, Toufiq ^a   Elgammal, Ahmed ^a  

^a RUTGERS UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

IMAGE PROCESSING; IMAGING SYSTEMS;

AFFINITY MATRIX; BIPARTITION; CLUSTERING RESULTS; DATA SETS; DATAPOINTS; GLOBAL SETTINGS; NEIGHBORHOOD INFORMATION; REAL IMAGES; ROBUST CLUSTERING; SIMILARITY MEASURE; TWO-POINT; VOTING APPROACH; VOTING METHOD;

CLUSTERING ALGORITHMS;

EID: 77951940238     PISSN: 15224880     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICIP.2009.5414180     Document Type: Conference Paper

References (8)

1. Andrew Ng, Michael Jordan, and Yair Weiss, "On spectral clustering: Analysis and an algorithm," in NIPS, 2002.
2. Jianbo Shi and Jitendra Malik, "Normalized cuts and image segmentation," PAMI, vol. 22, no. 8, 2000.
3. Ravi Kannan, Santosh Vempala, and Adrian Vetta, "On clusterings: Good, bad, and spectral," in FOCS, Nov. 2000.
4. Lihi Zelnik-Manor and Pietro Perona, "Self-tuning spectral clustering," in NIPS, 2004.
5. Boaz Nadler and Meirav Galun, "Fundamental limitations of spectral clustering," in NIPS, 2006.
6. A. Atrehl and J. Ghosh, "Cluster ensembles- a knowledge resue framework for combining multiple partitions," JMLR, vol. 3, no. Dec, pp. 583-617, 1997.
7. A. Fred and A. K. Jain, "Combining multiple clusterings using evidence accumulation," in ICPR, 2002, vol. IV, pp. 276-280.
8. Anirban Dasgupta, John Hopcroft, Ravi Kannan, and Pradipta Mitra, "Spectral clustering by recursive partitioning," in European Symposium on Algorithms, 2006.