• Corpus ID: 15032800

Secure Smartphone Unlock : Robust Face Spoof Detection on Mobile

  title={Secure Smartphone Unlock : Robust Face Spoof Detection on Mobile},
  author={Keyurkumar Patel and Hu Han and Anil K. Jain},
With the wide deployment of face recognition systems in applications from de-duplication to mobile device unlocking, security against face spoofing attacks requires increased attention; such attacks can be easily launched via printed photos, video replays and 3D masks of a face. We address the problem of facial spoof detection against print (photo) and replay (photo or video) attacks based on the analysis of image aliasing (e.g., surface reflection, moiré pattern, color distortion, and shape… 
Face/Fingerphoto Spoof Detection under Noisy Conditions by using Deep Convolutional Neural Network
This research first investigates local texture based anti-spoofing methods including existing popular methods (but changing some of the parameters) by using publicly available spoofed face/finger photo/video databases, and investigates the spoof detection under the camera defocus or hand movements during image capturing.
Presentation Attack Detection Methods for Face Recognition Systems
This paper describes the various aspects of face presentation attacks, including different types of face artifacts, state-of-the-art PAD algorithms and an overview of the respective research labs working in this domain, vulnerability assessments and performance evaluation metrics, the outcomes of competitions, the availability of public databases for benchmarking new P AD algorithms in a reproducible manner, and a summary of the relevant international standardization in this field.
Guillermo Estrada Domech An Assessment of Presentation Attack Detection Methods for Face Recognition Systems
This dissertation analyzes, evaluates and compares some of the most relevant, state-of-the-art feature-based methods for facial PAD in a variety of conditions, considering three of the facial spoofing databases publicly available 3DMAD, REPLAYMOBILE and OULU-NPU.


Live face video vs. spoof face video: Use of moiré patterns to detect replay video attacks
This work addresses the problem of facial spoofing detection against replay attacks based on the analysis of aliasing in spoof face videos and shows that the proposed approach is very effective in face spoof detection for both cross-database, and intra-database testing scenarios.
Spoofing in 2D face recognition with 3D masks and anti-spoofing with Kinect
  • N. Erdogmus, S. Marcel
  • Computer Science
    2013 IEEE Sixth International Conference on Biometrics: Theory, Applications and Systems (BTAS)
  • 2013
The 3D Mask Attack Database (3DMAD), the first publicly available 3D spoofing database, recorded with a low-cost depth camera is introduced and it is shown that easily attainable facial masks can pose a serious threat to 2D face recognition systems and LBP is a powerful weapon to eliminate it.
Spoofing Face Recognition With 3D Masks
This paper inspects the spoofing potential of subject-specific 3D facial masks for different recognition systems and addresses the detection problem of this more complex attack type.
Face Spoof Detection With Image Distortion Analysis
An efficient and rather robust face spoof detection algorithm based on image distortion analysis (IDA) that outperforms the state-of-the-art methods in spoof detection and highlights the difficulty in separating genuine and spoof faces, especially in cross-database and cross-device scenarios.
Detection of Face Spoofing Using Visual Dynamics
This work advances the state of the art in facial antispoofing by applying a recently developed algorithm called dynamic mode decomposition (DMD) as a general purpose, entirely data-driven approach to capture the above liveness cues.
On the effectiveness of local binary patterns in face anti-spoofing
This paper inspects the potential of texture features based on Local Binary Patterns (LBP) and their variations on three types of attacks: printed photographs, and photos and videos displayed on electronic screens of different sizes and concludes that LBP show moderate discriminability when confronted with a wide set of attack types.
Using Visual Rhythms for Detecting Video-Based Facial Spoof Attacks
This paper presents an algorithm for video-based spoofing attack detection through the analysis of global information which is invariant to content, since it takes advantage of noise signatures generated by the recaptured video to distinguish between fake and valid access videos.
Face spoofing detection from single images using micro-texture analysis
This work presents a novel approach based on analyzing facial image textures for detecting whether there is a live person in front of the camera or a face print, and analyzes the texture of the facial images using multi-scale local binary patterns (LBP).
Face Spoofing Detection Through Visual Codebooks of Spectral Temporal Cubes
This paper introduces a low cost and software-based method for detecting spoofing attempts in face recognition systems and extracts time-spectral feature descriptors from the video that can be understood as a low-level feature descriptor that gathers temporal and spectral information across the biometric sample.
Computationally Efficient Face Spoofing Detection with Motion Magnification
A new approach for spoofing detection in face videos using motion magnification using Eulerian motion magnification approach, which improves the state-of-art performance, especially HOOF descriptor yielding a near perfect half total error rate.