Audio-visual person authentication using lip-motion from orientation maps
Pattern Recognition Letters
Synergy of Lip-Motion and Acoustic Features in Biometric Speech and Speaker Recognition
IEEE Transactions on Computers
EURASIP Journal on Advances in Signal Processing
Non-intrusive liveness detection by face images
Image and Vision Computing
Dynamic tongueprint: A novel biometric identifier
Pattern Recognition
Real-time face detection using illumination invariant features
SCIA'07 Proceedings of the 15th Scandinavian conference on Image analysis
Text driven face-video synthesis using GMM and spatial correlation
SCIA'07 Proceedings of the 15th Scandinavian conference on Image analysis
Lip biometrics for digit recognition
CAIP'07 Proceedings of the 12th international conference on Computer analysis of images and patterns
TIR/VIS correlation for liveness detection in face recognition
CAIP'11 Proceedings of the 14th international conference on Computer analysis of images and patterns - Volume Part II
Blinking-based live face detection using conditional random fields
ICB'07 Proceedings of the 2007 international conference on Advances in Biometrics
Pyramid based interpolation for face-video playback in audio visual recognition
ICB'07 Proceedings of the 2007 international conference on Advances in Biometrics
Speaker and digit recognition by audio-visual lip biometrics
ICB'07 Proceedings of the 2007 international conference on Advances in Biometrics
A taxonomy of biometric system vulnerabilities and defences
International Journal of Biometrics
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A technique evaluating liveness in short face image sequences is presented. The intended purpose of the proposed system is to assist in a biometric authentication framework, by adding liveness awareness in a non-intrusive manner. Analysing the trajectories of single parts of a live face reveal valuable information to discriminate it against a spoofed one. The proposed system uses a lightweight novel optical flow, which is especially applicable in face motion estimation based on the structure tensor and a few frames. It uses a model-based local Gabor decomposition and SVM experts for face part detection. An alternative approach for face part detection using optical flow pattern matching is introduced as well. Experimental results on the proposed system are presented.