A Detection Method of Temporally Operated Videos Using Robust Hashing

08/10/2022
by   Shoko Niwa, et al.
0

SNS providers are known to carry out the recompression and resizing of uploaded videos/images, but most conventional methods for detecting tampered videos/images are not robust enough against such operations. In addition, videos are temporally operated such as the insertion of new frames and the permutation of frames, of which operations are difficult to be detected by using conventional methods. Accordingly, in this paper, we propose a novel method with a robust hashing algorithm for detecting temporally operated videos even when applying resizing and compression to the videos.

READ FULL TEXT

page 2

page 3

research
09/01/2022

Delving into the Frequency: Temporally Consistent Human Motion Transfer in the Fourier Space

Human motion transfer refers to synthesizing photo-realistic and tempora...
research
02/02/2021

Fake-image detection with Robust Hashing

In this paper, we investigate whether robust hashing has a possibility t...
research
01/09/2021

Detecting, Localising and Classifying Polyps from Colonoscopy Videos using Deep Learning

In this paper, we propose and analyse a system that can automatically de...
research
04/18/2018

Temporal Unknown Incremental Clustering (TUIC) Model for Analysis of Traffic Surveillance Videos

Optimized scene representation is an important characteristic of a frame...
research
09/03/2020

Robust Homomorphic Video Hashing

The Internet has been weaponized to carry out cybercriminal activities a...
research
11/27/2019

LucidDream: Controlled Temporally-Consistent DeepDream on Videos

In this work, we aim to propose a set of techniques to improve the contr...
research
01/21/2020

Detecting Face2Face Facial Reenactment in Videos

Visual content has become the primary source of information, as evident ...

Please sign up or login with your details

Forgot password? Click here to reset