Multilinear Analysis of Image Ensembles: TensorFaces

  • Authors:
  • M. A. O. Vasilescu;Demetri Terzopoulos

  • Affiliations:
  • -;-

  • Venue:
  • ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
  • Year:
  • 2002

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Abstract

Natural images are the composite consequence of multiple factors related to scene structure, illumination, and imaging. Multilinear algebra, the algebra of higher-order tensors, offers a potent mathematical framework for analyzing the multifactor structure of image ensembles and for addressing the difficult problem of disentangling the constituent factors or modes. Our multilinear modeling technique employs a tensor extension of the conventional matrix singular value decomposition (SVD), known as the N-mode SVD. As a concrete example, we consider the multilinear analysis of ensembles of facial images that combine several modes, including different facial geometries (people), expressions, head poses, and lighting conditions. Our resulting "TensorFaces" representation has several advantages over conventional eigenfaces. More generally, multilinear analysis shows promise as a unifying framework for a variety of computer vision problems.