Edge Detection and Linear Feature Extraction Using a 2-D Random Field Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
Application of the Karhunen-Loeve Procedure for the Characterization of Human Faces
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face recognition using a hybrid supervised/unsupervised neural network
Pattern Recognition Letters
Probabilistic Visual Learning for Object Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Recognition by Elastic Bunch Graph Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
Evaluation and comparison of different segmentation algorithms
Pattern Recognition Letters
Preprocessing of face images: detection of features and pose normalization
Computer Vision and Image Understanding
Image Segmentation by Unifying Region and Boundary Information
IEEE Transactions on Pattern Analysis and Machine Intelligence
History, Current Status, and Future of Infrared Identification
CVBVS '00 Proceedings of the IEEE Workshop on Computer Vision Beyond the Visible Spectrum: Methods and Applications (CVBVS 2000)
Comparison of visible and infra-red imagery for face recognition
FG '96 Proceedings of the 2nd International Conference on Automatic Face and Gesture Recognition (FG '96)
Robust Multi-Sensor Image Alignment
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Face recognition with visible and thermal infrared imagery
Computer Vision and Image Understanding - Special issue on Face recognition
Journal of Cognitive Neuroscience
AVBPA'05 Proceedings of the 5th international conference on Audio- and Video-Based Biometric Person Authentication
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An IR image of the human face presents its unique heat-signature and can be used for recognition. The characteristics of IR images maintain advantages over visible light images, and can be used to improve algorithms of human face recognition in several aspects. IR images are obviously invariant under extreme lighting conditions (including complete darkness). The main findings of this research are that IR face images are less effected by changes of pose or facial expression and enable a simple method for detection of facial features. In this paper we explore several aspects of face recognition in IR images. First, we compare the effect of varying environment conditions over IR and visible light images through a case study. Finally, we propose a method for automatic face recognition in IR images, through which we use a preprocessing algorithm for detecting facial elements, and show the applicability of commonly used face recognition methods in the visible light domain.