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...
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...
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...
Motionanalysis often relies on differencing operations that inherently amplify noise and are hindered by the spatial correspondenceproblem.Analternative approach is proposedusing ...
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 ...