Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital Image Processing: PIKS Inside
Digital Image Processing: PIKS Inside
Face Recognition by Elastic Bunch Graph Matching
CAIP '97 Proceedings of the 7th International Conference on Computer Analysis of Images and Patterns
Journal of Cognitive Neuroscience
Component-based face recognition with 3D morphable models
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
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
Mouth center detection under active near infrared illumination
SIP'07 Proceedings of the 6th Conference on 6th WSEAS International Conference on Signal Processing - Volume 6
A Biological Intelligent Access Control System Based on DSP and NIR Technology
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues
Drunk person identification using thermal infrared images
DSP'09 Proceedings of the 16th international conference on Digital Signal Processing
Facial expression recognition from near-infrared videos
Image and Vision Computing
Drunk person identification using thermal infrared images
International Journal of Electronic Security and Digital Forensics
Nighttime face recognition at long distance: cross-distance and cross-spectral matching
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part II
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Face recognition is a challenging visual classification task, especially when the lighting conditions can not be controlled. In this paper, we present an automatic face recognition system in the near infrared (IR) spectrum instead of the visible band. By making use of the near infrared band, it is possible for the system to work under very dark visual illumination conditions. A simple hardware enables efficient eye localization, thus the face can be easily detected based on the position of the eyes. This system exploits the feature extraction capabilities of the Discrete Cosine Transform (DCT) which can be calculated very fast. Support Vector Machines (SVMs) are used for classification. The effectiveness of our system is verified by experimental results.