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ICIP
2007
IEEE
14 years 10 months ago
MAP Particle Selection in Shape-Based Object Tracking
The Bayesian filtering for recursive state estimation and the shape-based matching methods are two of the most commonly used approaches for target tracking. The Multiple Hypothesi...
Alessio Dore, Carlo S. Regazzoni, Mirko Musso
ICASSP
2009
IEEE
13 years 6 months ago
Blind sparse source separation for unknown number of sources using Gaussian mixture model fitting with Dirichlet prior
In this paper, we propose a novel sparse source separation method that can be applied even if the number of sources is unknown. Recently, many sparse source separation approaches ...
Shoko Araki, Tomohiro Nakatani, Hiroshi Sawada, Sh...
SIBGRAPI
1999
IEEE
14 years 29 days ago
Speckle Noise MAP Filtering Based on Local Adaptive Neighborhood Statistics
This work proposes the use of an adaptive neighborhood procedure to extract local statistical properties of images in order to improve a speckle noise "Maximum a Posteriori &q...
Fátima N. S. de Medeiros, Nelson D. A. Masc...
CORR
2007
Springer
128views Education» more  CORR 2007»
13 years 8 months ago
Model Selection Through Sparse Maximum Likelihood Estimation
We consider the problem of estimating the parameters of a Gaussian or binary distribution in such a way that the resulting undirected graphical model is sparse. Our approach is to...
Onureena Banerjee, Laurent El Ghaoui, Alexandre d'...
NIPS
1998
13 years 10 months ago
Probabilistic Image Sensor Fusion
We present a probabilistic method for fusion of images produced by multiple sensors. The approach is based on an image formation model in which the sensor images are noisy, locall...
Ravi K. Sharma, Todd K. Leen, Misha Pavel