Title :
A SIFT-Kalman information fusion tracking algorithm based on PCA
Author :
Zhou Kai ; Fan Rui-xia ; Li Wei-xing
Author_Institution :
Sch. of Autom., Beijing Inst. of Technol., Beijing, China
Abstract :
In order to ensure the accuracy of vehicle tracking in the situation of similar background, the SIFT algorithm is proposed. Meanwhile, the PCA algorithm is used to reduce the dimensionality of SIFT descriptors to improve the system´s real-time and a SIFT-Kalman information fusion tracking algorithm based on PCA is set up. The results of experiments showed the proposed algorithm performs well when the object is cluttered.
Keywords :
Kalman filters; image fusion; optical tracking; principal component analysis; road vehicles; traffic engineering computing; PCA algorithm; SIFT algorithm; SIFT descriptor; SIFT-Kalman information fusion tracking; principal component analysis; vehicle tracking; Computer vision; Conferences; Educational institutions; Kalman filters; Pattern recognition; Principal component analysis; Vehicles; Kalman Filter; PCA; SIFT; Vehicle Tracking;
Conference_Titel :
Intelligent Control and Automation (WCICA), 2010 8th World Congress on
Conference_Location :
Jinan
Print_ISBN :
978-1-4244-6712-9
DOI :
10.1109/WCICA.2010.5554734
