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TSP
2008
97views more  TSP 2008»
13 years 7 months ago
Risk-Sensitive Particle Filters for Mitigating Sample Impoverishment
Risk-sensitive filters (RSF) put a penalty to higher-order moments of the estimation error compared to conventional filters as the Kalman filter minimizing the mean square error. ...
Umut Orguner, Fredrik Gustafsson
CVPR
2006
IEEE
14 years 9 months ago
Scalable Monocular SLAM
Localization and mapping in unknown environments becomes more difficult as the complexity of the environment increases. With conventional techniques, the cost of maintaining estim...
Ethan Eade, Tom Drummond
JUCS
2006
107views more  JUCS 2006»
13 years 7 months ago
Sequential Data Assimilation: Information Fusion of a Numerical Simulation and Large Scale Observation Data
: Data assimilation is a method of combining an imperfect simulation model and a number of incomplete observation data. Sequential data assimilation is a data assimilation in which...
Kazuyuki Nakamura, Tomoyuki Higuchi, Naoki Hirose
ICIP
2010
IEEE
13 years 10 months ago
Bacteria Filters: Persistent Particle Filters for Background Subtraction
Yair Movshovitz-Attias, Shmuel Peleg
ECCV
2006
Springer
14 years 9 months ago
Globally Optimal Active Contours, Sequential Monte Carlo and On-Line Learning for Vessel Segmentation
In this paper we propose a Particle Filter-based propagation approach for the segmentation of vascular structures in 3D volumes. Because of pathologies and inhomogeneities, many de...
Charles Florin, Nikos Paragios, James Williams