Title :
Visual Detection and Tracking of Moving Objects
Author :
Hamza Ergezer;Kemal Leblebicioglu
Author_Institution :
ASELSAN A. ?., Mikroelektronik, G?d?m ve Elektro-Optik Grubu, Ankara
fDate :
6/1/2007 12:00:00 AM
Abstract :
In this paper, primary steps of a visual surveillance system are presented: moving object detection and tracking of these moving objects. Running average method has been used to detect the moving objects in the video, which is taken from a static camera. Tracking of foreground objects has been realized by using a Kalman filter. After background subtraction, morphological operators are used to remove noises detected as foreground. Active contour models (snakes) are the segmentation tools for the extracted foregrounds. Snakes have been also used as an extra tool for object tracking.
Keywords :
"Object detection","Gaussian processes","Kalman filters","Surveillance","Cameras","Background noise","Active contours"
Conference_Titel :
Signal Processing and Communications Applications, 2007. SIU 2007. IEEE 15th
Print_ISBN :
1-4244-0719-2
DOI :
10.1109/SIU.2007.4298624