Compression-robust detection of Motion-Compensated Frame Interpolation using Discrete Cosine Transform in logarithm domain

Abstract

Motion Compensated Frame Interpolation (MCFI) is a widely used technique to improve the frame rate of a video sequence in recent years, but it can also be used by forgers for malicious forgery, resulting in a large number of fake high-frame-rate videos. This paper presents how the Discrete Cosine Transform (DCT) is used in the logarithm domain to identify whether a video has been forged by MCFI. First, the DCT is taken on each frame in a suspect video. Then, the DCT coefficients are transformed into the logarithm domain. Finally, the mean of the logarithmic DCT coefficients is computed, and its variation over time is taken as the DCT feature to derive a classifier to realize automatic detection. Since MCFI modifies the majority of DCT coefficients in the high-frequency band, the high-frequency DCT coefficients are significantly enhanced by the logarithm transform, making the DCT feature more sensitive to MCFI modification. More importantly, it is proved through quantitative and qualitative analyses that the proposed DCT feature has the capacity for resisting lossy compression. The proposed DCT feature is used to train different classifiers with a large-scale dataset, and the extensive experiments verify that the proposed DCT feature compares favorably with the state-of-the-art methods while having the robustness to lossy compression.