VGG-16-Based Framework for Identification of Facemask Using Video Forensics

2021 ◽  
pp. 673-685
Author(s):  
Sunpreet Kaur Nanda ◽  
Deepika Ghai ◽  
Sagar Pande
Keyword(s):  
Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 3953
Author(s):  
Han Pu ◽  
Tianqiang Huang ◽  
Bin Weng ◽  
Feng Ye ◽  
Chenbin Zhao

Digital video forensics plays a vital role in judicial forensics, media reports, e-commerce, finance, and public security. Although many methods have been developed, there is currently no efficient solution to real-life videos with illumination noises and jitter noises. To solve this issue, we propose a detection method that adapts to brightness and jitter for video inter-frame forgery. For videos with severe brightness changes, we relax the brightness constancy constraint and adopt intensity normalization to propose a new optical flow algorithm. For videos with large jitter noises, we introduce motion entropy to detect the jitter and extract the stable feature of texture changes fraction for double-checking. Experimental results show that, compared with previous algorithms, the proposed method is more accurate and robust for videos with significant brightness variance or videos with heavy jitter on public benchmark datasets.


IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 76937-76948 ◽  
Author(s):  
Brian C. Hosler ◽  
Xinwei Zhao ◽  
Owen Mayer ◽  
Chen Chen ◽  
James A. Shackleford ◽  
...  

2020 ◽  
Vol 112 (2) ◽  
pp. 1281-1302 ◽  
Author(s):  
Harpreet Kaur ◽  
Neeru Jindal

Author(s):  
Simone Milani ◽  
Marco Fontani ◽  
Paolo Bestagini ◽  
Mauro Barni ◽  
Alessandro Piva ◽  
...  

The broad availability of tools for the acquisition and processing of multimedia signals has recently led to the concern that images and videos cannot be considered a trustworthy evidence, since they can be altered rather easily. This possibility raises the need to verify whether a multimedia content, which can be downloaded from the internet, acquired by a video surveillance system, or received by a digital TV broadcaster, is original or not. To cope with these issues, signal processing experts have been investigating effective video forensic strategies aimed at reconstructing the processing history of the video data under investigation and validating their origins. The key assumption of these techniques is that most alterations are not reversible and leave in the reconstructed signal some “footprints”, which can be analyzed in order to identify the previous processing steps. This paper presents an overview of the video forensic techniques that have been proposed in the literature, focusing on the acquisition, compression, and editing operations, trying to highlight strengths and weaknesses of each solution. It also provides a review of simple processing chains that combine different operations. Anti-forensic techniques are also considered to outline the current limitations and highlight the open research issues.


2019 ◽  
Vol 75 ◽  
pp. 199-200
Author(s):  
Roberto Caldelli ◽  
Marc Chaumont ◽  
Chang-Tsun Li ◽  
Irene Amerini

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