Title :
Recursively estimating optical flow from a noisy image sequence
Author :
Jiang, Min ; Wu, Zhong-Quan ; Wu, You-Shou
Author_Institution :
Inf.-Electron. Dept., Tsinghua Univ., Beijing, China
Abstract :
A token-based method for recursively estimating optical flow from a noisy image sequence is presented. Motion characteristics of the perspective projection of a 3D moving object are analyzed and a dynamic model is built. The recursive solution is achieved through an iterated extended Kalman filter and two schemes for the velocity propagation of match points are discussed. Experimental results indicate that this method, which requires a long image sequence but rather few match points, is efficient and robust even in very poor conditions
Keywords :
Kalman filters; filtering and prediction theory; iterative methods; noise; pattern recognition; picture processing; 3D moving object; dynamic model; iterated extended Kalman filter; match points; noisy image sequence; optical flow; pattern recognition; perspective projection; picture processing; recursive estimation; token-based method; velocity propagation; Convergence; Coordinate measuring machines; Equations; Image motion analysis; Image sampling; Image sequences; Optical imaging; Optical noise; Recursive estimation; State estimation;
Conference_Titel :
Pattern Recognition, 1988., 9th International Conference on
Conference_Location :
Rome
Print_ISBN :
0-8186-0878-1
DOI :
10.1109/ICPR.1988.28391
