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» Continuous Gaussian Mixture Modeling
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NIPS
2004
14 years 11 months ago
Parametric Embedding for Class Visualization
In this paper, we propose a new method, Parametric Embedding (PE), for visualizing the posteriors estimated over a mixture model. PE simultaneously embeds both objects and their c...
Tomoharu Iwata, Kazumi Saito, Naonori Ueda, Sean S...
ICCV
2003
IEEE
15 years 11 months ago
Bayesian Clustering of Optical Flow Fields
We present a method for unsupervised learning of classes of motions in video. We project optical flow fields to a complete, orthogonal, a-priori set of basis functions in a probab...
Jesse Hoey, James J. Little
ICIP
2005
IEEE
15 years 11 months ago
Variational segmentation of color images
A variational Bayesian framework is employed in the paper for image segmentation using color clustering. A Gaussian mixture model is used to represent color distributions. Variati...
Nikolaos Nasios, Adrian G. Bors
ICML
2005
IEEE
15 years 10 months ago
Incomplete-data classification using logistic regression
A logistic regression classification algorithm is developed for problems in which the feature vectors may be missing data (features). Single or multiple imputation for the missing...
David Williams, Xuejun Liao, Ya Xue, Lawrence Cari...
ICASSP
2008
IEEE
15 years 4 months ago
Voice source cepstrum coefficients for speaker identification
We propose a novel feature set for speaker recognition that is based on the voice source signal. The feature extraction process uses closed-phase LPC analysis to estimate the voca...
Jon Gudnason, Mike Brookes