The current approaches to feature point correspondence are based on the hypothesis that the displacements for feature points between consecutive frames are small. That is

there is very short time interval between successive two frames in image sequences. These approaches are difficult to find the corresponding feature points when the time interval is large. In the paper

a new approach to feature point correspondence is proposed. It includes two steps. First

approximate location of feature points of moving targets can be obtained using polar-exponential grid sampling and log-polar coordinate mapping. The parameters of feature point position

including translation

rotation and scale

are got in log-polar coordinate and Cartesian coordinate. Then the corresponding feature points can be got with available traditional means

because feature points corresponding when the time interval is large turns into feature points corresponding when the time interval is small by the first step of the approach. The best advantage of the method is simple and efficient. In the paper

the principle of the method is introduced and the result of experiment is given. It turns out that the problem of feature point correspondence can be finally solved when the time interval between consecutive frames in image sequences is large

and that the first step of the approach is enough to resolve feature point correspondence of plane object moving.