Centralized Multiple-View Information Fusion for Multi-Object Tracking Using Labeled Multi-Bernoulli Filters

2018 ◽  
Author(s):  
Amirali Khodadadian Gostar ◽  
Tharindu Rathnayake ◽  
Alireza Bab-Hadiashar ◽  
Giorgi Battistelli ◽  
Luigi Chisci ◽  
...  
Keyword(s):  
Object Tracking ◽  
Information Fusion ◽  
Multiple View

Particle-filter-based object tracking with color and texture information fusion

2009 ◽  
Author(s):  
RuiQing Chen ◽  
ZhaoHui Zhang ◽  
HanQing Lu ◽  
HuiQing Cui ◽  
YuKun Yan
Keyword(s):  
Particle Filter ◽  
Object Tracking ◽  
Information Fusion ◽  
Texture Information

scholarly journals Physics and human-based information fusion for improved resident space object tracking

2018 ◽  
Vol 62 (7) ◽  
pp. 1800-1812 ◽  
Author(s):  
Emmanuel Delande ◽  
Jérémie Houssineau ◽  
Moriba Jah
Keyword(s):  
Object Tracking ◽  
Information Fusion ◽  
Space Object ◽  
Space Object Tracking

scholarly journals Object Tracking Using Information Fusion

2008 ◽  
Vol 18 (5) ◽  
pp. 666-671
Author(s):  
Jin-Hyung Lee ◽  
Seong-Won Jo ◽  
Jae-Min Kim ◽  
Sun-Tae Chung
Keyword(s):  
Object Tracking ◽  
Information Fusion

Study on Particle Filter Object Tracking Based on Weighted Fusion

2011 ◽  
Vol 403-408 ◽  
pp. 3049-3053
Author(s):  
Zhi Qiang Wen ◽  
Yan Hui Zhu ◽  
Zhao Yi Peng
Keyword(s):  
Particle Filter ◽  
Object Tracking ◽  
Linear Model ◽  
Information Fusion ◽  
Measurement Model ◽  
Color Histogram ◽  
Motion Information ◽  
Color Information ◽  
Model Based ◽  
Weighted Fusion

For the lack of self-adaptivity to environments, a measurement model based on weighted information fusion is presented in particle filter. Combined with color information and movement information of object, color histogram and motion Information histogram are built respectively, and then present a weighted linear model as the measurement model. The center-around method is adopted to compute the weight in the linear model. Lastly, a mass of experiments show the presented method be effective.

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