Polling Mechanism for Video Deepfake
Journal
Proceedings of the 3rd IEEE Eurasia Conference on IOT, Communication and Engineering 2021, ECICE 2021
Pages
320-323
Date Issued
2021
Author(s)
Abstract
A polling-based mechanism is developed to identify whether a video is forged. It is important for forensic image processing. However, most of the existing video deepfake algorithms are frame-based. In other words, a learning-based method is applied to identify whether a frame is forged then the mean of the fake score for all frames is applied to determine whether the whole video is forged. In this work, we propose a polling mechanism to well integrate the deepfake score of each frame. We found that the misidentification of a deepfake algorithm usually occurs in the frame with drastic motion, a tilted head, and blinking eyes. Therefore, we determine the weights of each frame according to the frame difference, the head orientation, whether the eyes are blinking, and the accuracy rate of the validation data. With the proposed polling mechanism, the accuracy of video deepfake can be improved and whether a video is forged can be well determined using a much smaller number of frames. ? 2021 IEEE.
Subjects
forensic image processing
head orientation
motion
polling mechanism
video deepfake
Digital forensics
Accuracy rate
Forensic image processing
Frame differences
Frame-based
Head orientation
Images processing
Learning-based methods
Motion
Polling mechanism
Video deepfake
Video signal processing
SDGs
Type
conference paper