Detection of motion-compensated frame-rate up-conversion via optical flow-based prediction residue

Abstract

To increase the temporal continuity of low frame-rate videos, Motion-Compensated Frame-Rate Up-Conversion (MC-FRUC), which is a special frame based video editing manipulation, can be employed to synthesize new intermediate frame between two successive frames. However, MC-FRUC can also be utilized to fake high frame-rate videos causing the wastes of storage space or users misleading. Although existing MC-FRUC detectors can obtain desirable performance for uncompressed videos or compressed videos with high perceptual quality, theirs performance degrades when test videos are encoded with higher quantization parameters. To deal with this problem, this paper presents a new optical flow-based detection method. Our method is divided into four steps. First, the forward or backward optical flow map is estimated by optical flow algorithm between the candidate frame, and its previous frame or following frame, respectively. Second, the prediction residue is calculated on the basis of these estimated optical flow maps to eliminate the side effect of texture information in the non-motion regions and the motion regions. Third, Markov statistic features are extracted. Finally, these features are fed into the ensemble classifier for identification of interpolated frames. We test different types of MC-FRUC methods under higher quantization parameters, and the results have shown the effectiveness of the proposed method compared with the existing relative ones.