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» Clustering Moving Objects via Medoid Clusterings
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IDA
1999
Springer
13 years 12 months ago
3D Grand Tour for Multidimensional Data and Clusters
Grand tour is a method for viewing multidimensional data via linear projections onto a sequence of two dimensional subspaces and then moving continuously from one projection to the...
Li Yang
ICDM
2006
IEEE
110views Data Mining» more  ICDM 2006»
14 years 1 months ago
Manifold Clustering of Shapes
Shape clustering can significantly facilitate the automatic labeling of objects present in image collections. For example, it could outline the existing groups of pathological ce...
Dragomir Yankov, Eamonn J. Keogh
WSCG
2004
174views more  WSCG 2004»
13 years 9 months ago
Objects and Occlusion from Motion Labeling
The problem of segmenting color video sequences is addressed. Boundary motion and occlusion relations expressed by labeling rules are argued to be of key importance for segmentati...
Albert Akhriev, Alexander Bonch-Osmolovsky, Alexan...
JISE
2010
144views more  JISE 2010»
13 years 2 months ago
Variant Methods of Reduced Set Selection for Reduced Support Vector Machines
In dealing with large datasets the reduced support vector machine (RSVM) was proposed for the practical objective to overcome the computational difficulties as well as to reduce t...
Li-Jen Chien, Chien-Chung Chang, Yuh-Jye Lee
ECCV
1998
Springer
14 years 9 months ago
Concerning Bayesian Motion Segmentation, Model, Averaging, Matching and the Trifocal Tensor
Abstract. Motion segmentation involves identifying regions of the image that correspond to independently moving objects. The number of independently moving objects, and type of mot...
Philip H. S. Torr, Andrew Zisserman