Results 221 to 230 of about 175,081 (248)
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Implementation of SLAM by probability hypothesis density filter
Optics and Precision Engineering, 2011Traditional Simultaneous Localization and Mapping(SLAM) algorithm is lack of the ability to describe multiple sensor information accurately in a clutter environment,and it is prone to false data association.Therefore,this paper proposes a SLAM algorithm based on Probability Hypothesis Density(PHD) filter to deal with these problems.By taking the sensor
杜航原 DU Hang-yuan +3 more
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Gaussian mixture probability hypothesis density for visual people racking
2007 10th International Conference on Information Fusion, 2007This paper presents our work which involves the application of a recursive Bayesian filter, the Gaussian mixture probability hypothesis density (GMPHD) filter, to a visual tracking problem. Foreground objects are detected using statistical background modeling to obtain measurements which are input into the filter. The GMPHD filter explicitly models the
Ya-Dong Wang +3 more
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Gaussian mixture particle flow probability hypothesis density filter
2017 20th International Conference on Information Fusion (Fusion), 2017The probability hypothesis density (PHD) filter is a promising filter for multi-target tracking which propagates the posterior intensity of the multi-target state. In this paper, a Gaussian mixture particle flow PHD (GMPF-PHD) filter is proposed which uses a bank of particles to represent the Gaussian components in the Gaussian mixture PHD (GM-PHD ...
Mingjie Wang +3 more
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The Recursive Spectral Bisection Probability Hypothesis Density Filter
2019Particle filter (PF) is used for multi-target detection and tracking, especially in the context of variable tracking target numbers, high target mobility, and other complex environments, it is difficult to detect, estimate and track targets in these situations. This paper discusses the probability hypothesis density (PHD) filtering which is widely used
Ding Wang, Xu Tang, Qun Wan
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Stochastic Partitioning for Extended Object Probability Hypothesis Density Filters
2019 Sensor Data Fusion: Trends, Solutions, Applications (SDF), 2019This paper presents a new likelihood-based partitioning method of the measurement set for the extended object probability hypothesis density (PHD) filter framework. Recent work has mostly relied on heuristic partitioning methods that cluster the measurement data based on a distance measure between the single measurements.
Julian Böhler +3 more
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Improved Particle Implementation of the Probability Hypothesis Density Filter in Resampling
2012 IEEE 12th International Conference on Computer and Information Technology, 2012A novel particle-PHD filter algorithm is proposed to deal with the multi-target tracking. It takes into account the most recent measurements by the unscented Kalman filter, not in the step of proposal distribution generation as usual, but in resampling step, to enhance the efficiency of the particle sampling.
Xu Tang, Jian Zhou, Jian Huang, Ping Wei
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Clustering based box-particle probability hypothesis density filtering
2017 20th International Conference on Information Fusion (Fusion), 2017This paper investigates the box-particle filter for multi-target tracking, and proposes a clustering based box-particle implementation of PHD filter. A subdivision step is added before the estimation of states. Each box is divided into several sub-box based on the estimated number of targets. An equivalent set of particles can be extracted from the set
Wei Li 0087, Chongzhao Han
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Multiple model cardinalized probability hypothesis density filter
SPIE Proceedings, 2011The Probability Hypothesis Density (PHD) filter propagates the first-moment approximation to the multi-target Bayesian posterior distribution while the Cardinalized PHD (CPHD) filter propagates both the posterior likelihood of (an unlabeled) target state and the posterior probability mass function of the number of targets.
Ramona Georgescu, Peter Willett
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Gaussian Mixture Probability Hypothesis Density Filter with State-Dependent Probabilities
2021 European Control Conference (ECC), 2021Yi-Chieh Sun, Inseok Hwang 0002
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Probability hypothesis density filter with low detection probability
IET Conference Proceedings, 2021M. Wu +5 more
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