Misalignment-robust face recognition
Refereed conference paper presented and published in conference proceedings

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AbstractIn this paper, we study the problem of subspace-based face recognition under scenarios with spatial misalignments and/or image occlusions. For a given subspace, the embedding of a new datum and the underlying spatial misalignment parameters are simultaneously inferred by solving a constrained l(1) norm optimization problem, which minimizes the error between the misalignment-amended image and the image reconstructed from the given subspace along with its principal complementary subspace. A byproduct of this formulation is the capability to detect the underlying image occlusions. Extensive experiments on spatial misalignment estimation, image occlusion detection, and face recognition with spatial misalignments and image occlusions all validate the effectiveness of our proposed general formulation.
All Author(s) ListWang H, Yan SC, Huang T, Liu JZ, Tang XO
Name of ConferenceIEEE Conference on Computer Vision and Pattern Recognition
Start Date of Conference23/06/2008
End Date of Conference28/06/2008
Place of ConferenceAnchorage
Country/Region of ConferenceUnited States of America
Pages3591 - 3596
LanguagesEnglish-United Kingdom
Web of Science Subject CategoriesComputer Science; Computer Science, Artificial Intelligence; Imaging Science & Photographic Technology

Last updated on 2021-15-01 at 00:44