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• W2742433981 abstract "In this paper, a novel image moment-based model for extended object shape estimation and tracking is presented. A method to represent and estimate an elliptical shape using its image moments is first developed. The model of representing the shape of an object falls under the category of random hypersurface model (RHM) for extended object tracking. The moments are estimated using an unscented Kalman filter (UKF). Measurements of 2D points sampled from the object are used to estimate the shape. A measurement model for the UKF is derived based on the 2D locations of the feature points sampled from the object. Simulation results of the proposed image moment-based model are presented to estimate the shape of static ellipse, and of the moving ellipse." @default.
• W2742433981 created "2017-08-17" @default.
• W2742433981 creator A5034041737 @default.
• W2742433981 creator A5076083833 @default.
• W2742433981 date "2017-07-01" @default.
• W2742433981 modified "2023-09-25" @default.
• W2742433981 title "Image moment-based random hypersurface model for extended object tracking" @default.
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• W2742433981 doi "https://doi.org/10.23919/icif.2017.8009883" @default.
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