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» Clustering Moving Objects via Medoid Clusterings
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KDD
2009
ACM
217views Data Mining» more  KDD 2009»
14 years 6 months ago
Efficient anomaly monitoring over moving object trajectory streams
Lately there exist increasing demands for online abnormality monitoring over trajectory streams, which are obtained from moving object tracking devices. This problem is challengin...
Yingyi Bu, Lei Chen 0002, Ada Wai-Chee Fu, Dawei L...
CVPR
2012
IEEE
11 years 7 months ago
Higher order motion models and spectral clustering
Motion segmentation based on point trajectories can integrate information of a whole video shot to detect and separate moving objects. Commonly, similarities are defined between ...
Peter Ochs, Thomas Brox
ICPR
2004
IEEE
14 years 6 months ago
Extraction and Clustering of Motion Trajectories in Video
A system is described that tracks moving objects in a video dataset so as to extract a representation of the objects' 3D trajectories. The system then finds hierarchical clus...
Dan Buzan, George Kollios, Stan Sclaroff
CVPR
1997
IEEE
14 years 7 months ago
Tracking non-rigid, moving objects based on color cluster flow
In this contribution we present an algorithm for tracking non-rigid, moving objects in a sequence of colored images, which were recorded by a non-stationary camera. The applicatio...
Bernd Heisele, Ulrich Kressel, W. Ritter
SIGMOD
2011
ACM
269views Database» more  SIGMOD 2011»
12 years 8 months ago
Advancing data clustering via projective clustering ensembles
Projective Clustering Ensembles (PCE) are a very recent advance in data clustering research which combines the two powerful tools of clustering ensembles and projective clustering...
Francesco Gullo, Carlotta Domeniconi, Andrea Tagar...