Detection of Fake Facial Images and Changes in Real Facial Images

被引:0
|
作者
Bobulski, Janusz [1 ]
Kubanek, Mariusz [1 ]
机构
[1] Czestochowa Tech Univ, Dept Comp Sci, PL-42201 Czestochowa, Poland
关键词
Fake images; deep learning; convolutional neural networks;
D O I
10.1007/978-3-031-70819-0_9
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Computer Vision techniques are widely used in the entertainment industry, helping to create more realistic effects in games and movies. They can recognise objects, characters, and player movements in video games. This allows games to react to player behaviours more intelligently, providing more dynamic and engaging experiences. Additionally, applying deep learning techniques combined with Computer Vision supports generating automatic special effects, such as adding interactive effects to live broadcasts. Unfortunately, such methods can generate, modify, and falsify information, such as swapping faces in a photo or video recording. Social media has many counterfeits and modifications of content known as fake news. The article proposes a method for detecting modified, real facial images and artificially generated facial images based on convolutional neural networks. Our technique allows for classifying facial photos into one of three classes: real faces, real faces with applied modifications (using photo editing software), and artificially generated facial images.
引用
收藏
页码:110 / 122
页数:13
相关论文
共 50 条
  • [41] FATIGUE DETECTION BASED ON FACIAL IMAGES PROCESSED BY DIFFERENCE ALGORITHM
    Chen, Jia
    Tao, Yin
    Zhang, Dalong
    Liu, Xiaoli
    Fang, Zhen
    Zhou, Qinwu
    Zhang, Bo
    2017 13TH IASTED INTERNATIONAL CONFERENCE ON BIOMEDICAL ENGINEERING (BIOMED), 2017, : 208 - 211
  • [42] Feasible Human Emotion Detection from Facial Thermal Images
    Oguchi, Kimio
    Hayashi, Shohei
    WORLD CONGRESS ON ENGINEERING AND TECHNOLOGY; INNOVATION AND ITS SUSTAINABILITY 2018, 2020, : 81 - 88
  • [43] Face detection and facial personation prevention by using infrared images
    Hirayama, T
    Lew, KF
    Iwai, Y
    Yachida, M
    SICE 2004 ANNUAL CONFERENCE, VOLS 1-3, 2004, : 461 - 465
  • [44] Fuzzy Enhancement for Efficient Emotion Detection from Facial Images
    Bhattacherjee, Payal
    Ramya, M. M.
    SOFT COMPUTING FOR PROBLEM SOLVING, SOCPROS 2017, VOL 1, 2019, 816 : 63 - 77
  • [45] Automated facial feature detection from portrait and range images
    Jahanbin, Sina
    Bovik, Alan C.
    Choi, Hyohoon
    2008 IEEE SOUTHWEST SYMPOSIUM ON IMAGE ANALYSIS & INTERPRETATION, 2008, : 25 - +
  • [46] A Neural System for Acute Disease Detection from Facial Images
    Fusek, Radovan
    Kromer, Pavel
    ADVANCES IN INTELLIGENT NETWORKING AND COLLABORATIVE SYSTEMS, INCOS-2022, 2022, 527 : 413 - 421
  • [47] Automatic Face Segmentation and Facial Landmark Detection in Range Images
    Segundo, Mauricio Pamplona
    Silva, Luciano
    Pereira Bellon, Olga Regina
    Queirolo, Chaua C.
    IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 2010, 40 (05): : 1319 - 1330
  • [48] Improving Detection of DeepFakes through Facial Region Analysis in Images
    Alanazi, Fatimah
    Ushaw, Gary
    Morgan, Graham
    ELECTRONICS, 2024, 13 (01)
  • [49] Detection of Face and Facial Features in digital Images and Video Frames
    Beigzadeh, M.
    Vafadoost, M.
    2008 CAIRO INTERNATIONAL BIOMEDICAL ENGINEERING CONFERENCE, 2008, : 113 - 116
  • [50] An efficient parallel eye detection algorithm on facial color images
    Nasiri, Jalal A.
    Moulavi, M. Amir
    Gelyan, Sepideh Nazemi
    Deldari, Hossein
    Yazdi, H. Sadoghi
    Shargh, A. Eshghi
    PROCEEDINGS OF NINTH ACIS INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING, ARTIFICIAL INTELLIGENCE, NETWORKING AND PARALLEL/DISTRIBUTED COMPUTING, 2008, : 706 - +