Face Recognition Systems Under Morphing Attacks: A Survey
暂无分享,去创建一个
Christoph Busch | Christian Rathgeb | Ulrich Scherhag | Ralph Breithaupt | Johannes Merkle | C. Busch | C. Rathgeb | R. Breithaupt | U. Scherhag | J. Merkle
[1] D. W. Choi,et al. Image Morphing Using Mass-Spring System , 2011 .
[2] Scott Schaefer,et al. Image deformation using moving least squares , 2006, ACM Trans. Graph..
[3] Takeo Kanade,et al. Multi-PIE , 2008, 2008 8th IEEE International Conference on Automatic Face & Gesture Recognition.
[4] Xiaogang Wang,et al. Deep Learning Face Attributes in the Wild , 2014, 2015 IEEE International Conference on Computer Vision (ICCV).
[5] Dumitru Erhan,et al. Going deeper with convolutions , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[6] Davide Maltoni,et al. The magic passport , 2014, IEEE International Joint Conference on Biometrics.
[7] Sanjit K. Mitra,et al. No-reference video quality metric based on artifact measurements , 2005, IEEE International Conference on Image Processing 2005.
[8] J. L. Wayman,et al. Best practices in testing and reporting performance of biometric devices. , 2002 .
[9] Adam Schmidt,et al. The put face database , 2008 .
[10] Kiran B. Raja,et al. Detecting morphed face images , 2016, 2016 IEEE 8th International Conference on Biometrics Theory, Applications and Systems (BTAS).
[11] Sébastien Marcel,et al. Deeply vulnerable: a study of the robustness of face recognition to presentation attacks , 2018, IET Biom..
[12] Jun Wang,et al. A 3D facial expression database for facial behavior research , 2006, 7th International Conference on Automatic Face and Gesture Recognition (FGR06).
[13] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[14] Kiran B. Raja,et al. Transferable Deep-CNN Features for Detecting Digital and Print-Scanned Morphed Face Images , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).
[15] Mahadev Satyanarayanan,et al. OpenFace: A general-purpose face recognition library with mobile applications , 2016 .
[16] Ahmed M. Megreya,et al. Unfamiliar faces are not faces: Evidence from a matching task , 2006, Memory & cognition.
[17] Kiran B. Raja,et al. On the vulnerability of face recognition systems towards morphed face attacks , 2017, 2017 5th International Workshop on Biometrics and Forensics (IWBF).
[18] Naser Damer,et al. MorGAN: Recognition Vulnerability and Attack Detectability of Face Morphing Attacks Created by Generative Adversarial Network , 2018, 2018 IEEE 9th International Conference on Biometrics Theory, Applications and Systems (BTAS).
[19] A. Burton,et al. Passport Officers’ Errors in Face Matching , 2014, PloS one.
[20] Christoph Busch,et al. Detecting Morphed Face Images Using Facial Landmarks , 2018, ICISP.
[21] Manjunath V. Joshi,et al. Automatic target image detection for morphing , 2015, J. Vis. Commun. Image Represent..
[22] Heinrich Müller,et al. Image warping with scattered data interpolation , 1995, IEEE Computer Graphics and Applications.
[23] Ahmed M Megreya,et al. Matching faces to photographs: poor performance in eyewitness memory (without the memory). , 2008, Journal of experimental psychology. Applied.
[24] G. Pike,et al. When Seeing should not be Believing: Photographs, Credit Cards and Fraud , 1997 .
[25] Eli Shechtman,et al. Regenerative morphing , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[26] Sébastien Marcel,et al. Biometric Systems under Morphing Attacks: Assessment of Morphing Techniques and Vulnerability Reporting , 2017, 2017 International Conference of the Biometrics Special Interest Group (BIOSIG).
[27] Jian Sun,et al. Blessing of Dimensionality: High-Dimensional Feature and Its Efficient Compression for Face Verification , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.
[28] Davide Maltoni,et al. On the Effects of Image Alterations on Face Recognition Accuracy , 2016, Face Recognition Across the Imaging Spectrum.
[29] Patrick J. Flynn,et al. Overview of the face recognition grand challenge , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[30] Davide Maltoni,et al. On the Feasibility of Creating Double-Identity Fingerprints , 2017, IEEE Transactions on Information Forensics and Security.
[31] Christoph Busch,et al. On the feasibility of creating morphed iris-codes , 2017, 2017 IEEE International Joint Conference on Biometrics (IJCB).
[32] Olac Fuentes,et al. An Approach to Automatic Morphing of Face Images in Frontal View , 2004, MICAI.
[33] Jana Dittmann,et al. Modeling Attacks on Photo-ID Documents and Applying Media Forensics for the Detection of Facial Morphing , 2017, IH&MMSec.
[34] Harry Wechsler,et al. The FERET database and evaluation procedure for face-recognition algorithms , 1998, Image Vis. Comput..
[35] Christoph Busch,et al. Performance variation of morphed face image detection algorithms across different datasets , 2018, 2018 International Workshop on Biometrics and Forensics (IWBF).
[36] Jonathan Wu. Face Recognition Jammer using Image Morphing , 2011 .
[37] Bülent Sankur,et al. A comparative study of face landmarking techniques , 2013, EURASIP J. Image Video Process..
[38] Fei Yang,et al. Face morphing using 3D-aware appearance optimization , 2012, Graphics Interface.
[39] Weisi Lin,et al. A no-reference quality metric for measuring image blur , 2003, Seventh International Symposium on Signal Processing and Its Applications, 2003. Proceedings..
[40] Joshua Correll,et al. The Chicago face database: A free stimulus set of faces and norming data , 2015, Behavior research methods.
[41] Christoph Busch,et al. PRNU-based detection of morphed face images , 2018, 2018 International Workshop on Biometrics and Forensics (IWBF).
[42] Richa Singh,et al. SWAPPED! Digital face presentation attack detection via weighted local magnitude pattern , 2017, 2017 IEEE International Joint Conference on Biometrics (IJCB).
[43] Axel Mecklinger,et al. Picture database of morphed faces (MoFa) : technical report , 2005 .
[44] James Philbin,et al. FaceNet: A unified embedding for face recognition and clustering , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[45] Christoph Busch,et al. Predicting the vulnerability of biometric systems to attacks based on morphed biometric information , 2018, IET Biom..
[46] Ian Craw,et al. Finding Face Features , 1992, ECCV.
[47] Martin Bichsel. Automatic interpolation and recognition of face images by morphing , 1996, Proceedings of the Second International Conference on Automatic Face and Gesture Recognition.
[48] Andrew Zisserman,et al. Deep Face Recognition , 2015, BMVC.
[49] Davis E. King,et al. Dlib-ml: A Machine Learning Toolkit , 2009, J. Mach. Learn. Res..
[50] Christoph Busch,et al. Towards Detection of Morphed Face Images in Electronic Travel Documents , 2018, 2018 13th IAPR International Workshop on Document Analysis Systems (DAS).
[51] Jana Dittmann,et al. Automatic Generation and Detection of Visually Faultless Facial Morphs , 2017, VISIGRAPP.
[52] Ahmed M. Megreya,et al. Matching Face Images Taken on the Same Day or Months Apart: the Limitations of Photo ID , 2013 .
[53] Andrew Zisserman,et al. Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.
[54] Jing Liao,et al. Automating Image Morphing Using Structural Similarity on a Halfway Domain , 2014, ACM Trans. Graph..
[55] Christoph Busch,et al. Morph Deterction from Single Face Image: a Multi-Algorithm Fusion Approach , 2018, ICBEA '18.
[56] Robin S S Kramer,et al. Fraudulent ID using face morphs: Experiments on human and automatic recognition , 2017, PloS one.
[57] Andreas Uhl,et al. A survey on biometric cryptosystems and cancelable biometrics , 2011, EURASIP J. Inf. Secur..
[58] Sung Yong Shin,et al. Image metamorphosis using snakes and free-form deformations , 1995, SIGGRAPH.
[59] Kiran B. Raja,et al. Face morphing versus face averaging: Vulnerability and detection , 2017, 2017 IEEE International Joint Conference on Biometrics (IJCB).
[60] Raul Vicente-Garcia,et al. Morphing Detection Using a General- Purpose Face Recognition System , 2018, 2018 26th European Signal Processing Conference (EUSIPCO).
[61] Enhua Wu,et al. Robust image metamorphosis immune from ghost and blur , 2012, The Visual Computer.
[62] Josephine Sullivan,et al. One millisecond face alignment with an ensemble of regression trees , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[63] Christoph Busch,et al. PRNU Variance Analysis for Morphed Face Image Detection , 2018, 2018 IEEE 9th International Conference on Biometrics Theory, Applications and Systems (BTAS).
[64] Azriel Rosenfeld,et al. Face recognition: A literature survey , 2003, CSUR.
[65] Lucas Theis,et al. Fast Face-Swap Using Convolutional Neural Networks , 2016, 2017 IEEE International Conference on Computer Vision (ICCV).
[66] Fei Peng,et al. Face Morphing Detection Using Fourier Spectrum of Sensor Pattern Noise , 2018, 2018 IEEE International Conference on Multimedia and Expo (ICME).
[67] Matti Pietikäinen,et al. A comparative study of texture measures with classification based on featured distributions , 1996, Pattern Recognit..
[68] Anil K. Jain,et al. Biometric Template Protection: Bridging the performance gap between theory and practice , 2015, IEEE Signal Processing Magazine.
[69] Lei Zhang,et al. A Probabilistic Collaborative Representation Based Approach for Pattern Classification , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[70] Mislav Grgic,et al. SCface – surveillance cameras face database , 2011, Multimedia Tools and Applications.
[71] Arun Ross,et al. Mixing fingerprints for generating virtual identities , 2011, 2011 IEEE International Workshop on Information Forensics and Security.
[72] Anna Hilsmann,et al. Accurate and Robust Neural Networks for Security Related Applications Exampled by Face Morphing Attacks , 2018, ArXiv.
[73] Michael G. Strintzis,et al. Face Recognition , 2008, Encyclopedia of Multimedia.
[74] Andreas Wolf,et al. An Overview of Recent Advances in Assessing and Mitigating the Face Morphing Attack , 2018, 2018 26th European Signal Processing Conference (EUSIPCO).
[75] Aras Asaad. Automatic Detection of Image Morphing by Topology-based Analysis , 2018, 2018 26th European Signal Processing Conference (EUSIPCO).
[76] David J Robertson,et al. Detecting morphed passport photos: a training and individual differences approach , 2018, Cognitive research: principles and implications.
[77] Chi Fang,et al. Histogram of the oriented gradient for face recognition , 2011 .
[78] Mahmoud Al-Ayyoub,et al. Impact of digital fingerprint image quality on the fingerprint recognition accuracy , 2017, Multimedia Tools and Applications.
[79] Zhou Wang,et al. No-reference perceptual quality assessment of JPEG compressed images , 2002, Proceedings. International Conference on Image Processing.
[80] Pong C. Yuen,et al. On the Reconstruction of Face Images from Deep Face Templates , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[81] Aksh Patel. Image Morphing Algorithm: A Survey , 2015 .
[82] Aleix M. Martinez,et al. The AR face database , 1998 .
[83] Wen Gao,et al. The CAS-PEAL Large-Scale Chinese Face Database and Baseline Evaluations , 2008, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.
[84] Kiran B. Raja,et al. Detecting Face Morphing Attacks with Collaborative Representation of Steerable Features , 2018, CVIP.
[85] Davide Maltoni,et al. Face Demorphing , 2018, IEEE Transactions on Information Forensics and Security.
[86] Natalia A. Schmid,et al. Image quality assessment for iris biometric , 2006, SPIE Defense + Commercial Sensing.
[87] Paul Miller,et al. Verification of face identities from images captured on video. , 1999 .
[88] Matthijs C. Dorst. Distinctive Image Features from Scale-Invariant Keypoints , 2011 .
[89] C. Thomaz,et al. A new ranking method for principal components analysis and its application to face image analysis , 2010, Image Vis. Comput..
[90] Thomas W. Sederberg,et al. Free-form deformation of solid geometric models , 1986, SIGGRAPH.
[91] Anil K. Jain,et al. Fingerprint Quality Indices for Predicting Authentication Performance , 2005, AVBPA.
[92] Shree K. Nayar,et al. Face swapping: automatically replacing faces in photographs , 2008, SIGGRAPH 2008.
[93] Yajie Tian,et al. Handbook of face recognition , 2003 .
[94] Natalia A. Schmid,et al. Estimating and Fusing Quality Factors for Iris Biometric Images , 2010, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.
[95] Alan C. Bovik,et al. No-Reference Image Quality Assessment in the Spatial Domain , 2012, IEEE Transactions on Image Processing.
[96] Thaddeus Beier,et al. Feature-based image metamorphosis , 1998 .
[97] Tim Valentine,et al. CCTV on trial: Matching video images with the defendant in the dock , 2009 .
[98] Kun Zhou,et al. Hair Interpolation for Portrait Morphing , 2013, Comput. Graph. Forum.
[99] Anna Hilsmann,et al. Detection of Face Morphing Attacks by Deep Learning , 2017, IWDW.
[100] Sabah Jassim,et al. Topological Data Analysis for Image Tampering Detection , 2017, IWDW.
[101] Christoph Busch,et al. Is your biometric system robust to morphing attaeks? , 2017, 2017 5th International Workshop on Biometrics and Forensics (IWBF).
[102] Timothy F. Cootes,et al. Active Shape Models-Their Training and Application , 1995, Comput. Vis. Image Underst..
[103] Davide Maltoni,et al. Face demorphing in the presence of facial appearance variations , 2018, 2018 26th European Signal Processing Conference (EUSIPCO).
[104] Steven M. Seitz,et al. View morphing , 1996, SIGGRAPH.
[105] Anna Hilsmann,et al. Reflection Analysis for Face Morphing Attack Detection , 2018, 2018 26th European Signal Processing Conference (EUSIPCO).
[106] Norbert Krüger,et al. Face Recognition by Elastic Bunch Graph Matching , 1997, CAIP.
[107] Luuk J. Spreeuwers,et al. Towards Robust Evaluation of Face Morphing Detection , 2018, 2018 26th European Signal Processing Conference (EUSIPCO).
[108] George Wolberg,et al. Image morphing: a survey , 1998, The Visual Computer.
[109] Timothy F. Cootes,et al. Active Appearance Models , 2001, IEEE Trans. Pattern Anal. Mach. Intell..
[110] Jana Dittmann,et al. Generalized Benford's Law for Blind Detection of Morphed Face Images , 2018, IH&MMSec.
[111] Xi Chen,et al. CNNs Under Attack: On the Vulnerability of Deep Neural Networks Based Face Recognition to Image Morphing , 2017, IWDW.
[112] Simon Lucey,et al. Face alignment through subspace constrained mean-shifts , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[113] Esa Rahtu,et al. BSIF: Binarized statistical image features , 2012, Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012).
[114] Tom Neubert,et al. Face Morphing Detection: An Approach Based on Image Degradation Analysis , 2017, IWDW.
[115] Jana Dittmann,et al. Benchmarking face morphing forgery detection: Application of stirtrace for impact simulation of different processing steps , 2017, 2017 5th International Workshop on Biometrics and Forensics (IWBF).
[116] Deva Ramanan,et al. Face detection, pose estimation, and landmark localization in the wild , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.
[117] Luc Van Gool,et al. Speeded-Up Robust Features (SURF) , 2008, Comput. Vis. Image Underst..