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ICCV
2009
IEEE
1556views Computer Vision» more  ICCV 2009»
15 years 27 days ago
Kernel Methods for Weakly Supervised Mean Shift Clustering
Mean shift clustering is a powerful unsupervised data analysis technique which does not require prior knowledge of the number of clusters, and does not constrain the shape of th...
Oncel Tuzel, Fatih Porikli, Peter Meer
WACV
2005
IEEE
14 years 1 months ago
Multi-Layer Hierarchical Clustering of Pedestrian Trajectories for Automatic Counting of People in Video Sequences
In this paper we propose an approach to count the number of pedestrians, given a trajectory data set provided by a tracking system. The tracking process itself is treated as a bla...
David Biliotti, Gianluca Antonini, Jean-Philippe T...
MUE
2007
IEEE
190views Multimedia» more  MUE 2007»
14 years 2 months ago
On Clustering Multimedia Time Series Data Using K-Means and Dynamic Time Warping
After the generation of multimedia data turned digital, an explosion of interest in their data storage, retrieval, and processing has drastically increased. This includes videos, ...
Vit Niennattrakul, Chotirat Ann Ratanamahatana
ICDM
2010
IEEE
230views Data Mining» more  ICDM 2010»
13 years 5 months ago
Clustering Large Attributed Graphs: An Efficient Incremental Approach
In recent years, many networks have become available for analysis, including social networks, sensor networks, biological networks, etc. Graph clustering has shown its effectivenes...
Yang Zhou, Hong Cheng, Jeffrey Xu Yu
OSDI
2008
ACM
14 years 8 months ago
Error Log Processing for Accurate Failure Prediction
Error logs are a fruitful source of information both for diagnosis as well as for proactive fault handling ? however elaborate data preparation is necessary to filter out valuable...
Felix Salfner, Steffen Tschirpke