Recent advances in visual and infrared face recognition: a review

  • Authors:

  • Seong G. Kong;Jingu Heo;Besma R. Abidi;Joonki Paik;Mongi A. Abidi

  • Affiliations:

  • Imaging, Robotics, and Intelligent Systems Laboratory, Department of Electrical and Computer Engineering, The University of Tennessee, Knoxville, TN;Imaging, Robotics, and Intelligent Systems Laboratory, Department of Electrical and Computer Engineering, The University of Tennessee, Knoxville, TN;Imaging, Robotics, and Intelligent Systems Laboratory, Department of Electrical and Computer Engineering, The University of Tennessee, Knoxville, TN;Imaging, Robotics, and Intelligent Systems Laboratory, Department of Electrical and Computer Engineering, The University of Tennessee, Knoxville, TN;Imaging, Robotics, and Intelligent Systems Laboratory, Department of Electrical and Computer Engineering, The University of Tennessee, Knoxville, TN

  • Venue:
  • Computer Vision and Image Understanding
  • Year:
  • 2005

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Abstract

Face recognition is a rapidly growing research area due to increasing demands for security in commercial and law enforcement applications. This paper provides an up-to-date review of research efforts in face recognition techniques based on two-dimensional (2D) images in the visual and infrared (IR) spectra. Face recognition systems based on visual images have reached a significant level of maturity with some practical success. However, the performance of visual face recognition may degrade under poor illumination conditions or for subjects of various skin colors. IR imagery represents a viable alternative to visible imaging in the search for a robust and practical identification system. While visual face recognition systems perform relatively reliably under controlled illumination conditions, thermal IR face recognition systems are advantageous when there is no control over illumination or for detecting disguised faces. Face recognition using 3D images is another active area of face recognition, which provides robust face recognition with changes in pose. Recent research has also demonstrated that the fusion of different imaging modalities and spectral components can improve the overall performance of face recognition.