DocumentCode
2660802
Title
Algorithm of target tracking based on mean shift with RBF neural network
Author
Bin, Zhou ; Junzheng, Wang ; Jiali, Mao
Author_Institution
Sch. of Inf. Sci. & Technol., Beijing Inst. of Technol., Beijing
fYear
2008
fDate
16-18 July 2008
Firstpage
518
Lastpage
521
Abstract
The limitation of Mean Shift algorithm under crossing occlusion is analyzed. To solve this problem, a new tracking algorithm using Mean Shift with RBF neural network is proposed. According to the formal information about the objectpsilas location, the iteration start position is found with RBF neural network. And the objectpsilas real center is calculated by Mean Shift algorithm. Experimental results show that the proposal algorithm is stable to solve the crossing occlusion problem, and the iteration number is reduced.
Keywords
image motion analysis; object detection; radial basis function networks; target tracking; RBF neural network; crossing occlusion; mean shift algorithm; target tracking; Algorithm design and analysis; Information analysis; Information science; Neural networks; Proposals; Target tracking; Mean Shift algorithm; Motion object tracking; RBF neural network;
fLanguage
English
Publisher
ieee
Conference_Titel
Control Conference, 2008. CCC 2008. 27th Chinese
Conference_Location
Kunming
Print_ISBN
978-7-900719-70-6
Electronic_ISBN
978-7-900719-70-6
Type
conf
DOI
10.1109/CHICC.2008.4605198
Filename
4605198
Link To Document