Paper Info
Title
Detecting video frame rate up-conversion based on frame-level analysis of average texture variation.
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.
Year
DOI
Venue
2017
10.1007/s11042-016-3468-1
Multimedia Tools Appl.
Keywords
Field
DocType
Digital video forensics, Frame-rate up-conversion (FRUC), Motion compensated interpolation (MCI), Average texture variation (ATV)
Computer vision,Visual artifact,Pattern recognition,Computer science,Interpolation,Residual frame,Artificial intelligence,Frame rate,Motion interpolation,Up conversion,Periodic graph (geometry)
Journal
Volume
Issue
ISSN
76
6
1573-7721
Citations 
PageRank 
References 
6
0.40
19
Authors
5
Name
Order
Citations
PageRank
Min Xia1526.70
Gaobo Yang2705.89
Li Leida368460.56
Ran Li4306.80
Xingming Sun53457132.47