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  • Multilinear Projection For Face Recognition Via Canonical Decomposition
    multilinear projection algorithm that is based on an M-mode SVD To develop our new algorithm, we extend and formalize the definition of the mode-m product, the mode-m identity tensor, and the mode-m pseudo-inverse tensor We demonstrate our multilinear projection in the context of facial image recognition and compare its results in si-
  • Multilinear projection for face recognition via canonical decomposition . . .
    We demonstrate our multilinear projection in the context of facial image recognition and compare its results in simultaneously inferring the identity, view, illumination, etc , coefficient vectors of an unlabeled test image against those obtained using multilinear projection based on the M-mode SVD, as well as against the results obtained using
  • Multilinear Projection for Appearance-Based Recognition in the Tensor . . .
    We demonstrate our multilinear projection in the context of unconstrained facial image recognition, where the mode labels are the person identity, the view-point, the illumination, the expression, etc
  • Multilinear Image Analysis for Facial Recognition
    We apply multilinear algebra, the algebra of higher-order tensors, to obtain a parsimonious representation of facial image ensembles which separates these factors Our representation, called TensorFaces, yields improved facial recognition rates relative to standard eigenfaces
  • Research - M. Alex O. Vasilescu - MIT Media Lab
    Multilinear projection is applied to unconstrained facial image recognition, where the mode labels are person identity, viewpoint, illumination, etc "Multilinear Projection for Face Recognition via Canonical Decomposition ", M A O Vasilescu, In Proc Face and Gesture Conf (FG'11), 476-483
  • (PDF) Multilinear Projection For Face Recognition Via Canonical . . . web . . .
    The multilinear projection simultaneously maps an unlabeled image from the pixel space into multiple causal factors underlying image formation, including illumination, imaging, and scene structure For facial recognition, the
  • Multilinear projection for face recognition via canonical decomposition
    We demonstrate our multilinear projection in the context of facial image recognition and compare its results in simultaneously inferring the identity, view, illumination, etc , coefficient
  • Multilinear projection for face recognition via canonical decomposition
    A new multilinear projection algorithm for appearance-based recognition in a tensor framework based on the canonical decomposition of tensors is introduced and its results in simultaneously inferring the identity, view, illumination, etc , coefficient vectors of an unlabeled test image are compared
  • Results TensorFaces Recognition - MIT Media Lab
    Projection Operator Contribution Tensor – Rank-(1,1,1) povol +T where P (pixels) =T (pixels) Response Tensor ≈ 1 Compute the Projection Tensor: 2 Compute the Response Tensor: 3 Extract the coefficient vectors by factorizing the Response Tensor by using N-mode SVD Multilinear Projection observ mode ( ) observ mode p v l l v p d = o o
  • (PDF) Multilinear Projection for Appearance-Based Recognition in the . . .
    Our multilinear projection algorithm simultaneously projects an unlabeled test image into multiple constituent mode spaces spanned by learned, mode-specific basis sets in order to infer its





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