Title :
Mean shift based object tracking supported with adaptive Kalman filter
Author :
Turhan, Mehmet Murat ; Hanbay, Davut
Author_Institution :
Bilgisayar Muhendisligi Bolumu, Inonu Univ., Malatya, Turkey
Abstract :
In this paper, mean shift algorithm and adaptive Kalman filter have been both utilized to realize object tracking in video sequences. Mean shift algorithm cannot give good results when the position of the tracked object is changed rapidly between sequential frames or the tracked object is occluded. In this paper, the first position of the tracked object is predicted by Kalman filter then mean shift algorithm starts to seek the object in this position. Bhattacharyya coefficient which is obtained from mean shift algorithm, is used to instantly update Kalman filters error covariance matrix and determine whether object is occluded or not. Experimental results demonstrate that the proposed method has been more efficient technique as compared to standard mean shift algorithm in case of occlusion and fast object tracking.
Keywords :
adaptive Kalman filters; covariance matrices; object tracking; Bhattacharyya coefficient; adaptive Kalman filter; error covariance matrix; mean shift algorithm; mean shift based object tracking; sequential frames; video sequences; Algorithm design and analysis; Conferences; Kalman filters; Object tracking; Pattern analysis; Real-time systems; Adaptive Kalman Filter; Mean Shift Algorithm; Object Tracking;
Conference_Titel :
Signal Processing and Communications Applications Conference (SIU), 2015 23th
Conference_Location :
Malatya
DOI :
10.1109/SIU.2015.7130438