Object tracking algorithm based on particle filter with color and texture feature

Author(s):  
Dongsheng Ding ◽  
Zengru Jiang ◽  
Chengyuan Liu
2013 ◽  
Vol 457-458 ◽  
pp. 1294-1297
Author(s):  
Tao Zhang ◽  
Yu Qing Chen ◽  
Xiang Yu Yu

.In this paper, a video tracking approach based on particle filter is proposed. Texture information is used instead of color. In the proposed approach, gray cooccurrence matrices are used as the texture metric. Experimental results show that the proposed algorithm lead to better result than color feature-based particle filter-based video tracking algorithm and is an effective tool for complicated video tracking application.


2013 ◽  
Vol 385-386 ◽  
pp. 1484-1487
Author(s):  
En Zeng Dong ◽  
Li Ya Su ◽  
Yan Hong Fu

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.


2014 ◽  
Vol 926-930 ◽  
pp. 3141-3144 ◽  
Author(s):  
Jiai He ◽  
Yong Na Li

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.


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