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» Advances in Mixture Models
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MVA
2008
125views Computer Vision» more  MVA 2008»
13 years 9 months ago
Pearson-based mixture model for color object tracking
To track objects in video sequences, many studies have been done to characterize the target with respect to its color distribution. Most often, the Gaussian Mixture Model (GMM) is ...
William Ketchantang, Stéphane Derrode, Lion...
ISDA
2010
IEEE
13 years 7 months ago
Self-adaptive Gaussian mixture models for real-time video segmentation and background subtraction
The usage of Gaussian mixture models for video segmentation has been widely adopted. However, the main difficulty arises in choosing the best model complexity. High complex models ...
Nicola Greggio, Alexandre Bernardino, Cecilia Lasc...
SDM
2011
SIAM
233views Data Mining» more  SDM 2011»
13 years 21 days ago
Multi-Instance Mixture Models
Multi-instance (MI) learning is a variant of supervised learning where labeled examples consist of bags (i.e. multi-sets) of feature vectors instead of just a single feature vecto...
James R. Foulds, Padhraic Smyth
ICDM
2008
IEEE
193views Data Mining» more  ICDM 2008»
14 years 4 months ago
Multiplicative Mixture Models for Overlapping Clustering
The problem of overlapping clustering, where a point is allowed to belong to multiple clusters, is becoming increasingly important in a variety of applications. In this paper, we ...
Qiang Fu, Arindam Banerjee
NIPS
2003
13 years 11 months ago
Gene Expression Clustering with Functional Mixture Models
We propose a functional mixture model for simultaneous clustering and alignment of sets of curves measured on a discrete time grid. The model is specifically tailored to gene exp...
Darya Chudova, Christopher E. Hart, Eric Mjolsness...