2D Instantaneous Frequency-based Method for Motion Estimation using Total Variation

We present a first approach to a new method to compute the motion estimation in digital videos using the two-dimensional instantaneous frequency information computed using amplitude-modulation frequency-modulation (AMFM) methods. The optical flow vectors are computed using an iteratively reweighted norm for total variation (IRN-TV) algorithm. We compare the proposed method using synthetic videos versus a previous three-dimensional AM-FM based method and available motion estimation methods such as a phase-based, Horn-Schunck and the Lucas-Kanade methods. The results are promising producing a full density estimation with more accurate results than the other methods.