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» The Unscented Particle Filter
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ICPR
2008
IEEE
14 years 6 months ago
SVD based Kalman particle filter for robust visual tracking
Object tracking is one of the most important tasks in computer vision. The unscented particle filter algorithm has been extensively used to tackle this problem and achieved a grea...
Qingdi Wei, Weiming Hu, Xi Li, Xiaoqin Zhang, Yang...
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...
JCP
2008
161views more  JCP 2008»
13 years 5 months ago
Interacting Multiple Model Particle-type Filtering Approaches to Ground Target Tracking
Ground maneuvering target tracking is a class of nonlinear and/or no-Gaussian filtering problem. A new interacting multiple model unscented particle filter (IMMUPF) is presented to...
Ronghua Guo, Zheng Qin, Xiangnan Li, Junliang Chen
TROB
2008
164views more  TROB 2008»
13 years 5 months ago
Unscented FastSLAM: A Robust and Efficient Solution to the SLAM Problem
The Rao
Chanki Kim, R. Sakthivel, Wan Kyun Chung
ICRA
2007
IEEE
190views Robotics» more  ICRA 2007»
13 years 11 months ago
A UPF-UKF Framework For SLAM
— In this paper we propose a SLAM framework which is based on an algorithm that combines an Unscented Particle Filter (UPF) and Unscented Kalman Filters (UKFs). A UPF is used to ...
Xiang Wang, Hong Zhang