Motion estimation based on textural flow

Motion estimation is one of the basic problems in computer vision. A novel method based on textural flow was proposed in order to allow estimation of dense motion from image sequences.compared with the conventional optical flow method using the assumption of constant brightness, it offers better robustness, higher accuracy, and faster computational speed. Based on robust invariant image textural features, a texture motion equation and motion vectors were derived. Difference levels, matrix determinant and condition numbers were defined and then integrated to judge the accuracy and robustness of motion estimation. In implementing the algorithm, a classic Gabor filter band was used. The algorithm was tested with many different kinds of image sequences and the results compared with those of typical methods. The results showed that the proposed method is best used when the moving targets have unique textural features or the background is complex.