Skip to Main content Skip to Navigation
Conference papers

Video Forgery Detection by Bitstream Analysis

Hugo Jean Emmanuel Giguet 1 Christophe Charrier 1 
1 Equipe SAFE - Laboratoire GREYC - UMR6072
GREYC - Groupe de Recherche en Informatique, Image et Instrumentation de Caen
Abstract : In this paper, we propose a video tampering detection method based on bitstream analysis for videos in H.264 or MPEG-4 AVC format. This method aims at detecting inter-frame alterations: insertion, deletion, permutation, duplication. Features are extracted from the original bitstream. This method therefore does not require the decoding of the video, which improves the speed of analysis. The detection quality remains very significant in terms of binary detection, tampered / pristine video, with a F1 measure equal to 94.89. Concerning multiclass classification, F1 measure reaches 70.33 due to the difficulty to separate swap and duplication forgeries.
Complete list of metadata
Contributor : Giguet Emmanuel Connect in order to contact the contributor
Submitted on : Tuesday, September 13, 2022 - 12:46:48 PM
Last modification on : Thursday, September 22, 2022 - 4:52:48 AM


Files produced by the author(s)


  • HAL Id : hal-03776086, version 1


Hugo Jean, Emmanuel Giguet, Christophe Charrier. Video Forgery Detection by Bitstream Analysis. Colour and Visual Computing Symposium 2022 (CVCS 2022), Sep 2022, Gjøvik, Norway. ⟨hal-03776086⟩



Record views


Files downloads