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Computer Science > Computer Vision and Pattern Recognition

Title: Video shutter angle estimation using optical flow and linear blur

Abstract: 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
Subjects: Computer Vision and Pattern Recognition (cs.CV)
Journal reference: Proceedings of the 27th Computer Vision Winter Workshop, 2024, 57-65
Cite as: arXiv:2303.10247 [cs.CV]
  (or arXiv:2303.10247v2 [cs.CV] for this version)

Submission history

From: David Korcak [view email]
[v1] Fri, 17 Mar 2023 20:54:04 GMT (2688kb,D)
[v2] Wed, 17 Apr 2024 13:25:35 GMT (2752kb,D)

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