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

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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.

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Acknowledgments

This work is supported in part by the National Natural Science Foundation of China (61379143, 61232016, 61572183, U1405254), the Specialized Research Fund for the Doctoral Program of Higher Education (SRFDP) (20120161110014) and the S&T Program of Xuzhou City (XM13B119) and the PAPD fund. This paper is also supported in part by Southwest University for Nationalities for the Fundamental Research Funds for the Central Universities (82000742). The authors appreciate the nice help from Mr Moses Odero for improving the English usages.

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Authors and Affiliations

  1. School of Information Science and Engineering, Hunan University, Changsha, 410082, China

    Min Xia & Gaobo Yang

  2. College of Electrical and Information Engineering, Southwest University for Nationalities, Chengdu, 610041, China

    Min Xia

  3. School of Information and Electrical Engineering, China University of Mining and Technology, Xuzhou, 221116, China

    Leida Li

  4. School of Computer and Information Technology, Xinyang Normal University, Xinyang, 464000, China

    Ran Li

  5. School of Computer and Software, Nanjing University of Information Science and Technology, Nangjing, 210044, China

    Xingming Sun

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  1. Min Xia
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  2. Gaobo Yang
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  3. Leida Li
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  4. Ran Li
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  5. Xingming Sun
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Corresponding author

Correspondence to Gaobo Yang.

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Xia, M., Yang, G., Li, L. et al. Detecting video frame rate up-conversion based on frame-level analysis of average texture variation. Multimed Tools Appl 76, 8399–8421 (2017). https://doi.org/10.1007/s11042-016-3468-1

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  • DOI: https://doi.org/10.1007/s11042-016-3468-1

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