Particle Filtering Algorithm Based on Dynamic Multi-Feature Fusion

Wu Tao; Yong Sheng Xu; Xiao Yan Wang

doi:10.4028/www.scientific.net/AMM.741.373

Paper Titles

The Detection Method of Lane Line Based on the Improved Otsu Threshold Segmentation
p.354

Cooperative Artificial Fish Swarm Optimization
p.359

A Research on the Real-Time 3-D Imaging Technology and Multi-View Control Interface Design for the Attitude Motion Simulator
p.363

Image Restoration Based on Pulse Coupled Neural Network
p.368

Particle Filtering Algorithm Based on Dynamic Multi-Feature Fusion
p.373

Research on the Harris Algorithm of Feature Extraction for Moving Targets in the Video
p.378

Segmentation Algorithm of Three-Dimensional Point Cloud Data Based on Region Growing
p.382

Routing Algorithm in Wireless Sensor Networks Based on Multi-Optimization Function
p.386

Application of Kriging Surrogate Model in Performance Parameters Optimization of Excavator Cab Shock Absorbers
p.393

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 741Particle Filtering Algorithm Based on Dynamic...

Particle Filtering Algorithm Based on Dynamic Multi-Feature Fusion

Abstract:

The target tracking technology in image sequence is of great meanings in the military and civilian areas, by using Monte Carlo method to complete the Bayesian recursive, particle filter is widely used in the systems of non-linear and non - Gaussian and good results are gained. However, particle filter there are also disadvantages in terms of sample impoverishment, the choosing of proper proposal distribution, real time and so on. In this paper, the particle filter is utilized to in the feature fusion of the moving target, and the experimental results show that the proposed algorithm has certain effect both on the remission of the sample impoverishment and the enhancement of the tracking robustness.

You might also be interested in these eBooks

Engineering Solutions for Manufacturing Processes V

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volume 741)

Pages:

373-377

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.741.373

Citation:

Cite this paper

Online since:

March 2015

Authors:

Wu Tao*, Yong Sheng Xu, Xiao Yan Wang

Keywords:

Multi-Feature Fusion, Particle Filter, Target Tracking

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] Shiqiang Hu, Lianghong Jing. The Principle and Application of Particle Filter. The First Edition. Beijing, Science Press, (2001).

Google Scholar

[2] Xiaofeng Yang, Guilin Zhang. A Target Tracking Algorithm Based on Affine Transform Modle. Computer & Digital Engineering, 2005, 33.

Google Scholar

[12] .

Google Scholar

[3] Junding Sun, Yuanyuan Ma. Summary of Texture Feature Research. Computer Systems& Applications. 2010, 19.

Google Scholar

[6] .

Google Scholar

[4] Xiaoping Zhong, Jianru Xue. An Adaptive Fusion Strategy Based Multiple-Cue Tracking. Journal of Electronics & Information Technology, 2007, 29(5).

Google Scholar

[5] Xiaoyan Wang, Zhiwen Zhou and Tao Wu. The Design of Greenhouse Temperature Control System. 2014 International Conference on Frontiers of Manufacturing Science and Measuring Technology.

Google Scholar