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
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;
Conference_Titel :
Systems, Signals and Image Processing (IWSSIP), 2014 International Conference on
Conference_Location :
Dubrovnik