Identifying Video Forgery Process Using Optical Flow

Digital video tampering detection: An overview of passive techniques

“…Video inter-frame forgery detection based on Lucas Kanade optical flow between adjacent frames is proposed by (Chao et al, 2013) and (Wang et al, 2014b). In (Chao et al, 2013), the total optical flow values in the X direction of adjacent frames are almost the same for non-tampered videos which means the optical flow is consistent, likewise in the Y direction.…”

“…Fixed Frame repetition and spatiotemporal region duplication Residual computed between adjacent frames, crosscorrelation of residual (Bestagini et al, 2013b) Detection accuracy decreases with increase in compression Frame interpolation MVs, periodicity of squared prediction error (Bestagini et al, 2013a) Compression affects performance; fails to detect downsampling where interpolation factor >= 2 Frame insertion, deletion and duplication Optical flow (Wang et al, 2014b) Frame deletion accuracy is less; complicated backgrounds, frequent motions and compression affects performance Zernike Opponent chromaticity moments (ZOCM) (Liu and Huang, 2015) Good performance on camera in stationary or slow-moving mode; fails in dynamic background videos Frame repetition and deletion Motion energy at spatial region of interest (SROI), average object area and entropy (Gupta et al, 2015) Works well on videos with high motion content (Su et al, 2009) used MCEA for frame deletion detection, which is a side effect of the blocking impairment and motion-compensated prediction. This appears in video codecs where block-based motion-compensated prediction is used.…”

Video content authentication techniques: a comprehensive survey

“…Another optical-flow-based forgery detection technique was suggested in [63], where the authors first modeled the probability distributions of optical-flow variations for untampered video sequences by a Gaussian distribution. Any abnormality in the flow variations was considered to be an anomaly, and a statistical inference test (Grubb's test) was used to assign an anomaly score to the optical-flow patterns of every test video.…”

“…Table 3 [63,72] detect all three kinds of inter-frame forgeries. The results in Table 3 pertain to the outcomes of the experiments performed with respect to the specific kinds of forgeries each of these techniques detect.…”

Video Inter-frame Forgery Detection Approach for Surveillance and Mobile Recorded Videos

“…To overcome this limitation, the proposed technique utilizes two different features PRG and OFG to enable forgery detection in all kind of video sequences. The techniques proposed in [13], [27], [28] measured the movement in brightness pattern of individual frames and estimated Lucas-Kanade optical flow between adjacent frames. The discontinuity in the consistency of measured brightness pattern ensures the existence of tampering.…”