An Adaptive Object Tracking Algorithm Combined with Particle Filter and Tensor Subspace

2010 ◽  
Vol 39 (6) ◽  
pp. 1047-1052
Author(s):  
温静 WEN Jing ◽  
李洁 LI Jie ◽  
高新波 GAO Xin-bo
Keyword(s):  
Particle Filter ◽  
Object Tracking ◽  
Tracking Algorithm ◽  
Tensor Subspace

An Improved Tracking Algorithm Combing Color and LBP Texture Features Based on Particle Filter

2013 ◽  
Vol 385-386 ◽  
pp. 1484-1487
Author(s):  
En Zeng Dong ◽  
Li Ya Su ◽  
Yan Hong Fu
Keyword(s):  
Particle Filter ◽  
Object Tracking ◽  
Reference Model ◽  
Texture Features ◽  
Tracking Algorithm ◽  
Color Histogram ◽  
Experimental Results ◽  
Single Feature ◽  
Highly Effective

In this paper, an tracking algorithm combing color and LBP texture features based on particle filter is proposed to overcome the disadvantages of existing particle filter object tracking methods. A color histogram and a texture histogram were combined to build the objects reference model, effectively improving the accuracy of object tracking. Experimental results demonstrate that, compared with the method based on single feature, the proposed method is highly effective, valid and is practicable.

Particle Filter Object Tracking Algorithm Based on Color and Gradient

2014 ◽  
Vol 926-930 ◽  
pp. 3141-3144 ◽  
Author(s):  
Jiai He ◽  
Yong Na Li
Keyword(s):  
Particle Filter ◽  
Object Tracking ◽  
Target Tracking ◽  
Tracking Algorithm ◽  
Experimental Results ◽  
Weighted Fusion ◽  
Illumination Changes ◽  
Particle Filter Algorithm

With the robustness of a single color which is not high in standard particle filter tracking, a fusion of color and gradient particle filter algorithm is proposed. By the advantages of color described the target ’global and gradients described the shape of structure, they are weighted fusion to form a new integrated histogram and applied to the particle filter framework. The experimental results show that compared with the traditional particle filter algorithm, the text of the algorithm can achieve relatively reliable target tracking under complicated background and illumination changes, with better robustness and reliability.

A fast particle filter object tracking algorithm by dual features fusion

2014 ◽  
Author(s):  
Shou-wei Zhao ◽  
Wei-ming Wang ◽  
Sa-sa Ma ◽  
Yong Zhang ◽  
Ming Yu
Keyword(s):  
Particle Filter ◽  
Object Tracking ◽  
Tracking Algorithm ◽  
Fast Particle ◽  
Features Fusion
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