Image analysis – Applications – Personnel identification
Reexamination Certificate
2011-05-03
2011-05-03
Carter, Aaron W (Department: 2624)
Image analysis
Applications
Personnel identification
C382S155000, C382S159000, C382S181000, C382S190000
Reexamination Certificate
active
07936906
ABSTRACT:
Systems and methods are described for face recognition using discriminatively trained orthogonal rank one tensor projections. In an exemplary system, images are treated as tensors, rather than as conventional vectors of pixels. During runtime, the system designs visual features—embodied as tensor projections—that minimize intraclass differences between instances of the same face while maximizing interclass differences between the face and faces of different people. Tensor projections are pursued sequentially over a training set of images and take the form of a rank one tensor, i.e., the outer product of a set of vectors. An exemplary technique ensures that the tensor projections are orthogonal to one another, thereby increasing ability to generalize and discriminate image features over conventional techniques. Orthogonality among tensor projections is maintained by iteratively solving an ortho-constrained eigenvalue problem in one dimension of a tensor while solving unconstrained eigenvalue problems in additional dimensions of the tensor.
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Drucker Steven M.
Hua Gang
Revow Michael
Viola Paul A
Carter Aaron W
Koziol Stephen R
Lee & Hayes PLLC
Microsoft Corporation
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