Title :
A novel background modeling approach for accurate and real-time motion segmentation
Author :
Wang, Tao ; Chen, Gang ; Zhou, Huimin
Author_Institution :
Dept. of Autom., Univ. of Sci. & Technol. of China
Abstract :
Fast and accurate segmentation of moving objects in video sequences is a basic task in many computer vision and video analysis applications. This paper presents a novel method for background modeling based on the unscented Kalman filter (UKF) algorithm. In addition, shadow detection is conducted during motion segmentation. Experiments are performed under different conditions indoor and outdoor. The results show that the proposed algorithm is effective and efficient in background modeling and motion segmentation
Keywords :
Kalman filters; computer vision; image motion analysis; image segmentation; image sequences; video signal processing; computer vision; real-time motion segmentation; shadow detection; unscented Kalman filter; video analysis applications; video sequences; Application software; Automation; Computer vision; Gaussian distribution; Iterative algorithms; Layout; Lighting; Motion segmentation; State estimation; Video sequences;
Conference_Titel :
Signal Processing, 2006 8th International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-9736-3
Electronic_ISBN :
0-7803-9736-3
DOI :
10.1109/ICOSP.2006.345710
