An indoor adaptive global motion estimation method
Huiqing Zhang, Lin Gao · 2014
Aiming at the problem of redundancy phenomenon in the motor process of image matching feature points, we proposed a kind of global motion which use Kalman filter algorithm to estimate the overlapping areas of matching images. This algorithm only to extract the feature points in the overlapping area, part of the extracted feature points also proposed an effective combination of SUSAN-SURF algorithm. SURF retain the high efficiency and SUSAN has the outline information. And then SURF algorithm is effectively improved by using KNN to speed up image matching, determine the matching point to realize image registration. Finally the algorithm was verified by experiment, this global motion method can under the premise in accuracy, improve the real-time performance.