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Detecting video frame rate up-conversion based on frame-level analysis of average texture variation

Research paper by Min Xia, Gaobo Yang, Leida Li, Ran Li, Xingming Sun

Indexed on: 04 Apr '16Published on: 04 Apr '16Published in: Multimedia Tools and Applications



Abstract

Frame rate up-conversion (FRUC) refers to frame interpolation between adjacent video frames to increase the motion continuity of low frame rate video, which can improve the visual quality on hand-held displays. However, FRUC can also be used for video forgery purposes such as splicing two videos with different frame-rates. We found that most FRUC approaches introduce visual artifacts into texture regions of interpolated frames. Based on this observation, a two-stage blind detection approach is proposed for video FRUC based on the frame-level analysis of average texture variation (ATV). First, the ATV value is computed for each frame to obtain an ATV curve of candidate video. Second, the ATV curve is further processed to highlight its periodic property, which indicates the existence of FRUC operation and further estimates the original frame rate. Thus, the positions of interpolated frames can be inferred as well. Extensive experimental results show that the proposed forensics approach is efficient and effective for the detection of existing typical FRUC approaches such as linear frame averaging and motion-compensated interpolation (MCI). The detection performance is superior to the existing approaches in terms of time efficiency and detection accuracy.