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» Clustering Large Dynamic Datasets Using Exemplar Points
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CVPR
2008
IEEE
14 years 10 months ago
Articulated shape matching using Laplacian eigenfunctions and unsupervised point registration
Matching articulated shapes represented by voxel-sets reduces to maximal sub-graph isomorphism when each set is described by a weighted graph. Spectral graph theory can be used to...
Diana Mateus, Radu Horaud, David Knossow, Fabio Cu...
SDM
2003
SIAM
184views Data Mining» more  SDM 2003»
13 years 9 months ago
Finding Clusters of Different Sizes, Shapes, and Densities in Noisy, High Dimensional Data
The problem of finding clusters in data is challenging when clusters are of widely differing sizes, densities and shapes, and when the data contains large amounts of noise and out...
Levent Ertöz, Michael Steinbach, Vipin Kumar
SIGMOD
2004
ACM
140views Database» more  SIGMOD 2004»
14 years 8 months ago
Incremental and Effective Data Summarization for Dynamic Hierarchical Clustering
Mining informative patterns from very large, dynamically changing databases poses numerous interesting challenges. Data summarizations (e.g., data bubbles) have been proposed to c...
Corrine Cheng, Jörg Sander, Samer Nassar
DAWAK
2009
Springer
14 years 2 months ago
Dynamic Clustering-Based Estimation of Missing Values in Mixed Type Data
The appropriate choice of a method for imputation of missing data becomes especially important when the fraction of missing values is large and the data are of mixed type. The prop...
Vadim V. Ayuyev, Joseph Jupin, Philip W. Harris, Z...
CVPR
2012
IEEE
11 years 10 months ago
Scale resilient, rotation invariant articulated object matching
A novel method is proposed for matching articulated objects in cluttered videos. The method needs only a single exemplar image of the target object. Instead of using a small set o...
Hao Jiang, Tai-Peng Tian, Kun He, Stan Sclaroff