Title :
Motion Multi-Vehicle Recognition and Tracking in Stable Scene
Author :
Gao, Tao ; Liu, Zheng-guang ; Zhang, Jun
Author_Institution :
Sch. of Electr. Eng. & Autom., Tianjin Univ., Tianjin
Abstract :
A method for moving multi-target recognition and tracking in stable scene is presented. Optical flow is used to extract the velocity of pixels, and targets are recognized by combining motion character points obtained by binary discrete wavelet transforms (BDWT). A discrete kalman filter is used to track targets in the follow-up frames; the center and scale of tracking window are updated by a Mexico wavelet kernel function mean shift method which is embedded into the discrete kalman filter framework to stabilize the trajectories of the targets for robust tracking during mutual occlusion. The method is tested on several frame sequences and shown to achieve robust and reliable frame-rate recognition and tracking.
Keywords :
Kalman filters; discrete wavelet transforms; image motion analysis; object detection; object recognition; target tracking; Mexico wavelet kernel function; binary discrete wavelet transforms; discrete Kalman filter; frame-rate recognition; frame-rate tracking; motion character points; moving multitarget recognition; moving multivehicle recognition; stable scene tracking; Character recognition; Discrete wavelet transforms; Image motion analysis; Kernel; Layout; Optical filters; Robustness; Target recognition; Target tracking; Trajectory;
Conference_Titel :
Future Information Technology and Management Engineering, 2008. FITME '08. International Seminar on
Conference_Location :
Leicestershire, United Kingdom
Print_ISBN :
978-0-7695-3480-0
DOI :
10.1109/FITME.2008.112