Share Email Print
cover

Proceedings Paper • new

Detection of deleted frames on videos using a 3D convolutional neural network
Author(s): V. Voronin; R. Sizyakin; A. Zelensky; A. Nadykto; I. Svirin
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

Digital video forgery or manipulation is a modification of the digital video for fabrication, which includes frame sequence manipulations such as deleting, insertion and swapping. In this paper, we focus on the detection problem of deleted frames in videos. Frame dropping is a type of video manipulation where consecutive frames are deleted to skip content from the original video. The automatic detection of deleted frames is a challenging task in digital video forensics. This paper describes an approach using spatial-temporal analysis based on the convolution with a bank of 3D Gabor filters. Also, we use the 3D Convolutional Neural Network for frame drop detection for preprocessed frames. Experimental results demonstrate the effectiveness of the proposed approach on a test video database.

Paper Details

Date Published: 2 November 2018
PDF: 8 pages
Proc. SPIE 10802, Counterterrorism, Crime Fighting, Forensics, and Surveillance Technologies II, 108020U (2 November 2018); doi: 10.1117/12.2326806
Show Author Affiliations
V. Voronin, Don State Technical Univ. (Russian Federation)
R. Sizyakin, Don State Technical Univ. (Russian Federation)
A. Zelensky, Moscow State Univ. of Technology "STANKIN" (Russian Federation)
A. Nadykto, Moscow State Univ. of Technology "STANKIN" (Russian Federation)
I. Svirin, CJSC "Nordavind" (Russian Federation)


Published in SPIE Proceedings Vol. 10802:
Counterterrorism, Crime Fighting, Forensics, and Surveillance Technologies II
Henri Bouma; Radhakrishna Prabhu; Robert James Stokes; Yitzhak Yitzhaky, Editor(s)

© SPIE. Terms of Use
Back to Top