DocumentCode
159735
Title
Background subtraction-based multiple object tracking using particle filter
Author
Intaek Kim ; Awan, Tayyab Wahab ; Youngsung Soh
Author_Institution
Dept. of Inf. & Commun. Eng., Myongji Univ., Yongin, South Korea
fYear
2014
fDate
12-15 May 2014
Firstpage
71
Lastpage
74
Abstract
In surveillance system, many vision based methods are utilized for multiple objects. Some of the methods used for tracking include background modeling, Kalman filter, particle filter etc. The proposed method combines both the background modeling and particle filter to track multiple objects. This method consists of two steps: background subtraction and application of particle filter. Background subtraction restricts the area of search so that the particle filter performs efficiently. Different colored particles are displayed on the object for tracking. After applying the proposed method on a video having multiple objects, successful results were obtained.
Keywords
Kalman filters; computer vision; object tracking; particle filtering (numerical methods); video surveillance; Kalman filter; background modeling; background subtraction-based multiple object tracking; particle filter; surveillance system; video; vision based methods; Business; Europe; Kalman filters; Tracking; Background Subtraction; Particle filter; Reference frame; Tracking using particles;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems, Signals and Image Processing (IWSSIP), 2014 International Conference on
Conference_Location
Dubrovnik
ISSN
2157-8672
Type
conf
Filename
6837633
Link To Document