Video shutter angle estimation using optical flow and linear blur
This addresses video analysis for forensic applications like detecting tampering, but it is incremental as it builds on existing optical flow and blur estimation techniques.
The paper tackles the problem of estimating shutter angle in videos with motion by relating exposure fraction to optical flow and linear motion blur, achieving a mean absolute error of 0.039 on a dataset with exposure fractions from 0.015 to 0.36.
We present a method for estimating the shutter angle, a.k.a. exposure fraction - the ratio of the exposure time and the reciprocal of frame rate - of videoclips containing motion. The approach exploits the relation of the exposure fraction, optical flow, and linear motion blur. Robustness is achieved by selecting image patches where both the optical flow and blur estimates are reliable, checking their consistency. The method was evaluated on the publicly available Beam-Splitter Dataset with a range of exposure fractions from 0.015 to 0.36. The best achieved mean absolute error of estimates was 0.039. We successfully test the suitability of the method for a forensic application of detection of video tampering by frame removal or insertion