Robust tracking method based on particle filter for crossing of targets with similar appearances

2012 ◽  
Author(s):  
Gaku Watanabe ◽  
Shinji Fukui ◽  
Keisuke Takechi ◽  
Yuji Iwahori ◽  
Robert J. Woodham
Keyword(s):  
Particle Filter ◽  
Robust Tracking ◽  
Tracking Method

scholarly journals Robust Tracking Method by Mean-Shift Using Spatiograms and Particle-Filter

2012 ◽  
Vol 78 (787) ◽  
pp. 799-811 ◽  
Author(s):  
Kazuki TADA ◽  
Ming DING ◽  
Hiroshi TAKEMURA ◽  
Hiroshi MIZOGUCHI
Keyword(s):  
Particle Filter ◽  
Mean Shift ◽  
Robust Tracking ◽  
Tracking Method

Robust tracking algorithm based on multi-feature fusion and particle filter

2010 ◽  
Vol 30 (3) ◽  
pp. 643-645 ◽  
Author(s):  
Wei ZENG ◽  
Gui-bin ZHU ◽  
Jie CHEN ◽  
Ding-ding TANG
Keyword(s):  
Particle Filter ◽  
Feature Fusion ◽  
Tracking Algorithm ◽  
Robust Tracking

Tracking method of space IR small target based on improved particle filter

2010 ◽  
Vol 24 (11) ◽  
pp. 1007-1011
Author(s):  
Xuezhi Xiang ◽  
Yu Peng ◽  
Zhiying Han ◽  
Zhihong Xi
Keyword(s):  
Particle Filter ◽  
Small Target ◽  
Tracking Method

Robust Autonomous Car-Like Robot Tracking Based on Tracking-Learning-Detection

2014 ◽  
Vol 687-691 ◽  
pp. 564-571 ◽  
Author(s):  
Lin Bao Xu ◽  
Shu Ming Tang ◽  
Jin Feng Yang ◽  
Yan Min Dong
Keyword(s):  
Optical Flow ◽  
Fast Moving ◽  
Moving Objects ◽  
Tracking Algorithm ◽  
Robust Tracking ◽  
Symmetry Detection ◽  
Tracking Method ◽  
Robot Tracking ◽  
Improve Accuracy ◽  
First Time

This paper proposes a robust tracking algorithm for an autonomous car-like robot, and this algorithm is based on the Tracking-Learning-Detection (TLD). In this paper, the TLD method is extended to track the autonomous car-like robot for the first time. In order to improve accuracy and robustness of the proposed algorithm, a method of symmetry detection of autonomous car-like robot rear is integrated into the TLD. Moreover, the Median-Flow tracker in TLD is improved with a pyramid-based optical flow tracking method to capture fast moving objects. Extensive experiments and comparisons show the robustness of the proposed method.

A Diffraction Measurement Model and Particle Filter Tracking Method for RSS-Based DFL

2015 ◽  
Vol 33 (11) ◽  
pp. 2391-2403 ◽  
Author(s):  
Zhenghuan Wang ◽  
Heng Liu ◽  
Shengxin Xu ◽  
Xiangyuan Bu ◽  
Jianping An
Keyword(s):  
Particle Filter ◽  
Measurement Model ◽  
Diffraction Measurement ◽  
Tracking Method
Sign in / Sign up

Export Citation Format

Share Document