IEEE Transactions on Pattern Analysis and Machine Intelligence
Two- and three-dimensional patterns of the face
Two- and three-dimensional patterns of the face
Combination of Face Classifiers for Person Identification
ICPR '96 Proceedings of the International Conference on Pattern Recognition (ICPR '96) Volume III-Volume 7276 - Volume 7276
Two-Dimensional PCA: A New Approach to Appearance-Based Face Representation and Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Recognition in Hyperspectral Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Indoor and Outdoor, Multimodal, Multispectral and Multi-Illuminant Database for Face Recognition
CVPRW '06 Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans - Special section: Best papers from the 2007 biometrics: Theory, applications, and systems (BTAS 07) conference
Eigenspace-based face recognition: a comparative study of different approaches
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Bidirectional PCA with assembled matrix distance metric for image recognition
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Application of majority voting to pattern recognition: an analysis of its behavior and performance
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Facial expression recognition from line-based caricatures
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Lighting aware preprocessing for face recognition across varying illumination
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part II
Face Recognition Using Kernel UDP
Neural Processing Letters
Sparse tensor embedding based multispectral face recognition
Neurocomputing
An approach to SWIR hyperspectral hand biometrics
Information Sciences: an International Journal
Hi-index | 0.00 |
This correspondence paper studies face recognition by using hyperspectral imagery in the visible light bands. The spectral measurements over the visible spectrum have different discriminatory information for the task of face identification, and it is found that the absorption bands related to hemoglobin are more discriminative than the other bands. Therefore, feature band selection based on the physical absorption characteristics of face skin is performed, and two feature band subsets are selected. Then, three methods are proposed for hyperspectral face recognition, including whole band (2D)2PCA, single band (2D)2PCA with decision level fusion, and band subset fusion-based (2D)2PCA. A simple yet efficient decision level fusion strategy is also proposed for the latter two methods. To testify the proposed techniques, a hyperspectral face database was established which contains 25 subjects and has 33 bands over the visible light spectrum (0.4-0.72 µm). The experimental results demonstrated that hyperspectral face recognition with the selected feature bands outperforms that by using a single band, using the whole bands, or, interestingly, using the conventional RGB color bands.