Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Method and system for detecting deep forged video based on optical flow method

A technology of video detection and optical flow method, applied in neural learning methods, character and pattern recognition, image data processing, etc., can solve the problem of strong dependence on pre-algorithms, failure of detection methods, and affecting the generalization ability of deep forgery detection algorithms, etc. problem, to achieve the effect of improving generalization ability and reducing strong dependence

Pending Publication Date: 2022-02-22
XIAMEN MEIYA PICO INFORMATION
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] In order to solve the technical problems in the prior art that the detection method based on the inconsistency of biological characteristics fails, the inter-frame detection algorithm has a strong dependence on the pre-algorithm, and affects the generalization ability of the deep forgery detection algorithm, the present invention proposes a method based on optical flow Deep fake video detection method and system to solve the above technical problems

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Method and system for detecting deep forged video based on optical flow method
  • Method and system for detecting deep forged video based on optical flow method
  • Method and system for detecting deep forged video based on optical flow method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0037] The application will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain related inventions, rather than to limit the invention. It should also be noted that, for the convenience of description, only the parts related to the related invention are shown in the drawings.

[0038] It should be noted that, in the case of no conflict, the embodiments in the present application and the features in the embodiments can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and embodiments.

[0039] According to an embodiment of the present application, a deep fake video detection method based on the optical flow method, figure 1 A flow chart of a method for detecting a deep fake video based on an optical flow method according to an embodiment of the present applic...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a method and a system for detecting a deep forged video based on an optical flow method. The method comprises the following steps: collecting a deep forged video and an original video which are tampered in different modes to respectively construct a training set and a verification set; performing frame extraction processing on the videos in the training set and the verification set to obtain each frame of image of each video, and extracting optical flow features by using an optical flow calculation model; splicing each frame of image and the optical flow features according to a time sequence, and inputting a neural network model for training until loss convergence; carrying out frame extraction processing, optical flow calculation and image splicing on the video to be verified, taking part of the image and sending the image to a neural network model, obtaining an output result mean value through an activation function of a neural network according to obtained output, and if the output result mean value is not smaller than a preset threshold value, determining the video to be verified to be a deep forged video. According to the method, the strong dependence of a deep counterfeit detection algorithm on a preposition algorithm can be reduced, meanwhile, various deep counterfeit videos can be effectively detected, and the generalization ability of the algorithm is improved.

Description

technical field [0001] The present invention relates to the technical field of fake video detection, in particular to a method and system for deep fake video detection based on the optical flow method. Background technique [0002] Deep forgery technology refers to the use of deep learning related technologies to tamper with or generate video, audio, images, etc. Different from traditional forgery technologies, deepfakes are easy to generalize and difficult to distinguish with the naked eye, and the threshold for ordinary people to forge after obtaining a deepfake model is low. Therefore, it has developed rapidly in the past two years, and the identification methods for deepfake videos have also become increasingly popular. Came into being. Since the current deepfake videos are often spliced ​​by multiple frames of forged images, in view of this feature, the mainstream deepfake video identification methods can be divided into two types, one is based on artificial visual eff...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06T3/40G06K9/62G06N3/04G06N3/08G06V10/774
CPCG06T7/0002G06T3/4038G06N3/08G06T2207/10016G06N3/045G06F18/214
Inventor 吴婷婷刘彩玲汪泰伸陈德意高志鹏张光斌赵建强李国庆
Owner XIAMEN MEIYA PICO INFORMATION
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products