Neural Network-Based Face Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Avoiding Replay-Attacks in a Face Recognition Systenm using Head-Pose Estimation
AMFG '03 Proceedings of the IEEE International Workshop on Analysis and Modeling of Faces and Gestures
Face recognition with visible and thermal infrared imagery
Computer Vision and Image Understanding - Special issue on Face recognition
Face recognition: A literature survey
ACM Computing Surveys (CSUR)
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
Evaluating Liveness by Face Images and the Structure Tensor
AUTOID '05 Proceedings of the Fourth IEEE Workshop on Automatic Identification Advanced Technologies
Infrared Human Face Auto Locating Based on SVM and A Smart Thermal Biometrics System
ISDA '06 Proceedings of the Sixth International Conference on Intelligent Systems Design and Applications - Volume 02
Physiology-Based Face Recognition in the Thermal Infrared Spectrum
IEEE Transactions on Pattern Analysis and Machine Intelligence
Illumination Invariant Face Recognition Using Near-Infrared Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
IR and visible light face recognition
Computer Vision and Image Understanding
Encyclopedia of Biometrics
Face liveness detection from a single image with sparse low rank bilinear discriminative model
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part VI
Real-Time Face Detection and Motion Analysis With Application in “Liveness” Assessment
IEEE Transactions on Information Forensics and Security - Part 2
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Face liveness detection in visible light (VIS) spectrum is facing great challenges. Beyond visible light spectrum, thermal IR (TIR) has intrinsic live signal itself. In this paper, we present a novel liveness detection approach based on thermal IR spectrum. Live face is modeled in the cross-modality of thermal IR and visible light spectrum. In our model, canonical correlation analysis between visible and thermal IR face is exploited. The correlation of different face parts is also investigated to illustrate more correlative features and be helpful to improve live face detection ability. An extensive set of liveness detection experiments are presented to show effectiveness of our approach and other correlation methods are also tested for comparison.