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WILF
2007
Springer
98views Fuzzy Logic» more  WILF 2007»
15 years 11 months ago
Possibilistic Clustering in Feature Space
In this paper we propose the Possibilistic C-Means in Feature Space and the One-Cluster Possibilistic C-Means in Feature Space algorithms which are kernel methods for clustering in...
Maurizio Filippone, Francesco Masulli, Stefano Rov...
159
Voted
PCM
2004
Springer
131views Multimedia» more  PCM 2004»
15 years 10 months ago
Vision-Based Sign Language Recognition Using Sign-Wise Tied Mixture HMM
Abstract. In this paper, a new sign-wise tied mixture HMM (SWTMHMM) is proposed and applied in vision-based sign language recognition (SLR). In the SWTMHMM, the mixture densities o...
Liangguo Zhang, Gaolin Fang, Wen Gao, Xilin Chen, ...
148
Voted
NIPS
2004
15 years 6 months ago
The Laplacian PDF Distance: A Cost Function for Clustering in a Kernel Feature Space
A new distance measure between probability density functions (pdfs) is introduced, which we refer to as the Laplacian pdf distance. The Laplacian pdf distance exhibits a remarkabl...
Robert Jenssen, Deniz Erdogmus, José Carlos...
120
Voted
FLAIRS
1998
15 years 6 months ago
Detecting Motion in Single Images Using ALISA
Motionanalysis often relies on differencing operations that inherently amplify noise and are hindered by the spatial correspondenceproblem.Analternative approach is proposedusing ...
Taras P. Riopka, Peter Bock
147
Voted
ICASSP
2010
IEEE
15 years 5 months ago
Hierarchical Gaussian Mixture Model
Gaussian mixture models (GMMs) are a convenient and essential tool for the estimation of probability density functions. Although GMMs are used in many research domains from image ...
Vincent Garcia, Frank Nielsen, Richard Nock