Title :
Fast locating with global probability density estimation
Author :
Zhou Bin ; Zhang Hui ; Zhang Bochuan
Author_Institution :
Nat. Lab. of Aerosp. Intell. Control Technol., Beijing, China
Abstract :
A fast locating algorithm with global probability density estimation is proposed to speed up the location process of the optical imaging guidance system. A monotonically decreasing sequence of bandwidths is obtained according to the size of target and the parameters of the guidance system. In the convergence process, with the smoothness effect of the large bandwidth, the compact of the local probability mode is avoided, and the precise position of the object could be found with the optimal bandwidth, which was similar to the object scale. The experimental results prove that the computation time cost is proportional to the convergence distance between the start and the real location. Especially, with higher guild precision, the new tracker proposed here works better.
Keywords :
convergence; estimation theory; image sequences; probability; convergence distance; convergence process; fast locating algorithm; global probability density estimation; location process; monotonically decreasing sequence; optical imaging guidance system; Aerospace control; Bandwidth; Convergence; Electronic mail; Estimation; Google; Optical imaging; Global probability density estimation; Mean shift (MS); object location; optical imaging guidance;
Conference_Titel :
Control and Decision Conference (CCDC), 2013 25th Chinese
Conference_Location :
Guiyang
Print_ISBN :
978-1-4673-5533-9
DOI :
10.1109/CCDC.2013.6561548