Toward hyperspectral face recognition

Face recognition continues to meet significant challenges in reaching accurate results and still remains one of the activities where humans outperform technology. An attractive approach in improving face identification is provided by the fusion of multiple imaging sources such as visible and infrared images. Hyperspectral data, i.e. images collected over hundreds of narrow contiguous light spectrum intervals constitute a natural choice for expanding face recognition image fusion, especially since it may provide information beyond the normal visible range, thus exceeding the normal human sensing. In this paper we investigate the efficiency of hyperspectral face recognition through an in house experiment that collected data in over 120 bands within the visible and near infrared range. The imagery was produced using an off the shelf sensor in both indoors and outdoors with the subjects being photographed from various angles. Further processing included spectra collection and feature extraction. Human matching performance based on spectral properties is discussed.

[1]  P. Jonathon Phillips.  Human identification technical challenges , 2002, Proceedings. International Conference on Image Processing.

[2]  Ioannis T. Pavlidis,et al.  Face Detection in the Near-IR Spectrum , 2003, Image Vis. Comput..

[3]  Erik Hjelmås,et al.  Face Detection: A Survey , 2001, Comput. Vis. Image Underst..

[4]  Azriel Rosenfeld,et al.  Face recognition: A literature survey , 2003, CSUR.

[5]  Joseph Wilder,et al.  Comparison of visible and infra-red imagery for face recognition , 1996, Proceedings of the Second International Conference on Automatic Face and Gesture Recognition.

[6]  Yi-Ting Chou.  Toward Face Detection , Pose Estimation and Human Recognition from Hyperspectral Imagery , 2004 .

[7]  Lawrence B. Wolff,et al.  Illumination invariant face recognition using thermal infrared imagery , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[8]  H.J.C.M. Sterenborg,et al.  Skin optics , 1989, IEEE Transactions on Biomedical Engineering.

[9]  Stefan A. Robila,et al.  Using spectral distances for speedup in hyperspectral image processing , 2005 .

[10]  Anuj Srivastava,et al.  Statistical hypothesis pruning for identifying faces from infrared images , 2003, Image Vis. Comput..

[11]  P. Wintz,et al.  Information Extraction, SNR Improvement, and Data Compression in Multispectral Imagery , 1973, IEEE Trans. Commun..

[12]  Erich N. Grossman,et al.  Passive hyperspectral terahertz imagery for security screening using a cryogenic microbolometer , 2005, SPIE Defense + Commercial Sensing.

[13]  Seong G. Kong,et al.  Recent advances in visual and infrared face recognition - a review , 2005, Comput. Vis. Image Underst..

[14]  Thomas S. Huang,et al.  Image processing , 1971 .

[15]  P. Jonathon Phillips.  Progress in Human ID , 2003, Proceedings of the IEEE Conference on Advanced Video and Signal Based Surveillance, 2003..

[16]  Elli Angelopoulou,et al.  Multispectral skin color modeling , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[17]  Ioannis Pavlidis,et al.  Face detection in the near-IR spectrum , 2003, SPIE Defense + Commercial Sensing.

[18]  Andreas Koschan,et al.  Multispectral Fusion for Indoor and Outdoor Face Authentication , 2006, 2006 Biometrics Symposium: Special Session on Research at the Biometric Consortium Conference.

[19]  Andrea Salgian,et al.  A comparative analysis of face recognition performance with visible and thermal infrared imagery , 2002, Object recognition supported by user interaction for service robots.

[20]  John Daugman,et al.  Face and Gesture Recognition: Overview , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

[21]  P. K Varshney,et al.  Advanced image processing techniques for remotely sensed hyperspectral data : with 128 figures and 30 tables , 2004 .

[22]  Mongi A. Abidi,et al.  An Indoor and Outdoor, Multimodal, Multispectral and Multi-Illuminant Database for Face Recognition , 2006, 2006 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'06).

[23]  Pawan Sinha,et al.  Face Recognition by Humans: Nineteen Results All Computer Vision Researchers Should Know About , 2006, Proceedings of the IEEE.

[24]  Bruce J. Tromberg,et al.  Face Recognition in Hyperspectral Images , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[25]  Chein-I. Chang.  Hyperspectral Imaging: Techniques for Spectral Detection and Classification , 2003 .