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ICPR
2006
IEEE
14 years 4 months ago
Exploiting High Dimensional Video Features Using Layered Gaussian Mixture Models
Analysis of video data usually requires training classifiers in high dimensional feature spaces. This paper proposes a layered Gaussian mixture model (LGMM) to exploit high dimens...
Datong Chen, Jie Yang
ICPR
2006
IEEE
14 years 4 months ago
EBEM: An Entropy-based EM Algorithm for Gaussian Mixture Models
Antonio Peñalver Benavent, Francisco Escola...
ICPR
2008
IEEE
14 years 4 months ago
Segmentation by combining parametric optical flow with a color model
We present a simple but efficient model for object segmentation in video scenes that integrates motion and color information in a joint probabilistic framework. Optical flow is mo...
Adrian Ulges, Thomas M. Breuel
ICIP
2001
IEEE
14 years 5 months ago
Supervised segmentation and tracking of nonrigid objects using a "mixture of histograms" model
Segmentation and tracking of objects in video sequences is important for a number of applications. In the supervised variant, segmentation can be achieved by modelling the probabi...
Mark Everingham, Barry T. Thomas
ICIP
2003
IEEE
14 years 5 months ago
A Bayesian framework for Gaussian mixture background modeling
Background subtraction is an essential processing component for many video applications. However, its development has largely been application driven and done in ad hoc manners. I...
Dar-Shyang Lee, Jonathan J. Hull, Berna Erol
ICIP
2007
IEEE
14 years 5 months ago
Robust Image Segmentation with Mixtures of Student's t-Distributions
Gaussian mixture models have been widely used in image segmentation. However, such models are sensitive to outliers. In this paper, we consider a robust model for image segmentati...
Giorgos Sfikas, Christophoros Nikou, Nikolas P. Ga...