Robust optical flow estimation

The paper presents a robust algorithm for computation of optical flow using the principle of conservation of a set of semi-invariant local features that are representatives of local gray-level properties in an image. Specifically, a set of rotation-invariant local orthogonal Zernike moments is used as features. These are inherently integral-based features, and therefore are robust against possible variations of intensity values that may occur over a sequence of images due to sensor noise, varying illumination etc. The 2D local optical flow field is obtained by the singular value decomposition of an overdetermined set of linear equations of velocity field components, resulting from the principle of conservation of features in a small neighborhood. The proposed approach is compared with Horn-Schunck (1981), and Lucas-Kanade´s optical flow techniques. Experimental results with synthetic as well as real sequences are presented to demonstrate the effectiveness of the proposed approach