Application of Moving Object Tracking Based on Kalman Filter Algorithm

2013 ◽  
Vol 13 (19) ◽  
pp. 4096-4098
Author(s):  
Xiao Zhansheng
Keyword(s):  
Kalman Filter ◽  
Object Tracking ◽  
Moving Object ◽  
Kalman Filter Algorithm ◽  
Moving Object Tracking

Video Tracking of Human with Occlusion Based on MeanShift and Kalman Filter

2013 ◽  
Vol 380-384 ◽  
pp. 3672-3677 ◽  
Author(s):  
Bao Hong Yuan ◽  
De Xiang Zhang ◽  
Kui Fu ◽  
Ling Jun Zhang
Keyword(s):  
Kalman Filter ◽  
Object Tracking ◽  
Moving Objects ◽  
Video Tracking ◽  
Moving Object ◽  
Large Area ◽  
Image Region ◽  
Future State ◽  
Kalman Filter Algorithm ◽  
Histogram Similarity

In order to accomplish tracking of moving objects requirements, and overcome the defect of occlusion in the process of tracking moving object, this paper presents a method which uses a combination of MeanShift and Kalman filter algorithm. MeanShift object tracking algorithm uses a histogram to describe the color characteristics of an object, and search the location of an image region that the color histogram is closest to the histogram of the object. Histogram similarity is defined in terms of the Bhattacharya coefficient. When the moving object is a large area blocked, the future state of moving object is estimated by Kalman filter. Experimental results verify that the proposed algorithm achieves efficient tracking of moving objects under the confusing situations.

Moving Object Tracking Using Kalman Filter

2018 ◽  
Author(s):  
Pramod R. Gunjal ◽  
Bhagyashri R. Gunjal ◽  
Haribhau A. Shinde ◽  
Swapnil M. Vanam ◽  
Sachin S. Aher
Keyword(s):  
Kalman Filter ◽  
Object Tracking ◽  
Moving Object ◽  
Moving Object Tracking
Sign in / Sign up

Export Citation Format

Share Document