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» Parametric contour tracking using unscented Kalman filter
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IPMI
2009
Springer
14 years 6 months ago
Neural Tractography Using An Unscented Kalman Filter
We describe a technique to simultaneously estimate a local neural fiber model and trace out its path. Existing techniques estimate the local fiber orientation at each voxel indepen...
James G. Malcolm, Martha Elizabeth Shenton, Yogesh...
IROS
2008
IEEE
211views Robotics» more  IROS 2008»
13 years 11 months ago
GP-BayesFilters: Bayesian filtering using Gaussian process prediction and observation models
Abstract— Bayesian filtering is a general framework for recursively estimating the state of a dynamical system. The most common instantiations of Bayes filters are Kalman filt...
Jonathan Ko, Dieter Fox
IJSR
2010
153views more  IJSR 2010»
13 years 2 months ago
A Bank of Unscented Kalman Filters for Multimodal Human Perception with Mobile Service Robots
A new generation of mobile service robots could be ready soon to operate in human environments if they can robustly estimate position and identity of surrounding people. Researcher...
Nicola Bellotto, Huosheng Hu
CVPR
2005
IEEE
14 years 7 months ago
Particle Filtering for Geometric Active Contours with Application to Tracking Moving and Deforming Objects
Geometric active contours are formulated in a manner which is parametrization independent. As such, they are amenable to representation as the zero level set of the graph of a hig...
Yogesh Rathi, Namrata Vaswani, Allen Tannenbaum, A...
AUSAI
2004
Springer
13 years 10 months ago
Enhanced Importance Sampling: Unscented Auxiliary Particle Filtering for Visual Tracking
Abstract. The particle filter has attracted considerable attention in visual tracking due to its relaxation of the linear and Gaussian restrictions in the state space model. It is...
Chunhua Shen, Anton van den Hengel, Anthony R. Dic...