Foreground Segmentation Improvement by Image Denoising Preprocessing Applied to Noisy Video Sequences

2021 ◽  
pp. 388-397
Author(s):  
Jorge García-Gozález ◽  
Juan Miguel Ortiz-de-Lazcano-Lobato ◽  
Rafael Marcos Luque-Baena ◽  
Ezequiel López-Rubio
Keyword(s):  
Image Denoising ◽  
Video Sequences ◽  
Foreground Segmentation

Detecting “DeepFakes” in H.264 Video Data Using Compression Ghost Artifacts

2020 ◽  
Vol 2020 (4) ◽  
pp. 116-1-116-7
Author(s):  
Raphael Antonius Frick ◽  
Sascha Zmudzinski ◽  
Martin Steinebach
Keyword(s):  
Image Forensics ◽  
Video Data ◽  
Experimental Results ◽  
Video Sequences ◽  
The Internet ◽  
Video Content ◽  
High Quality ◽  
The Public

In recent years, the number of forged videos circulating on the Internet has immensely increased. Software and services to create such forgeries have become more and more accessible to the public. In this regard, the risk of malicious use of forged videos has risen. This work proposes an approach based on the Ghost effect knwon from image forensics for detecting forgeries in videos that can replace faces in video sequences or change the mimic of a face. The experimental results show that the proposed approach is able to identify forgery in high-quality encoded video content.

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