IEEE Transactions on Aerospace and Electronic Systems · 2014 · 277 citations · 33 references
ComputingComputer ScienceComputational GeometryComputer VisionMachine VisionGeometry ProcessingShape AnalysisShape RepresentationSurface ReconstructionTracking SystemsVisual Tracking3D Object Tracking3D Visual TrackingModel-based TrackingShape ApproximationSurface Tracking
The random hypersurface model (RHM) is introduced for estimating a shape approximation of an extended object in addition to its kinematic state. An RHM represents the spatial extent by means of randomly scaled versions of the shape boundary. In doing so, the shape parameters and the measurements are related via a measurement equation that serves as the basis for a Gaussian state estimator. Specific estimators are derived for elliptic and star-convex shapes.
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Unscented Filtering and Nonlinear Estimation
Simon Julier, Jeffrey Uhlmann · Proceedings of the IEEE · 2004 · 6.5K citations
Computing, Data Science, Forecasting +14