Previous work has demonstrated that the image variations of many objects (human faces in particular) under variable lighting can be effectively modeled by low dimensional linear spaces. Basis images spanning this space are usually obtained in one of two ways: A large number of images of the object under different conditions is acquired, and principal component analysis (PCA) is used to estimate a subspace. Alternatively, a 3D model (perhaps reconstructed from images) is used to render virtual images under either point sources from which a subspace is derived using PCA or more recently under diffuse synthetic lighting based on spherical harmonics. In this paper we show that there exists a configuration of nine point light source directions such that by taking nine images of each individual under these single sources, the resulting subspace is effective at recognition under a wide range of lighting conditions. Since the subspace is generated directly from real images, potentially complex intermediate steps such as PCA and 3D reconstruction can be completely avoided; nor is it necessary to acquire large numbers of training images or physically construct complex diffuse (harmonic) light fields. We provide both theoretical and empirical results to explain why these linear spaces should be good for recognition.


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    Titel :

    Nine points of light: acquiring subspaces for face recognition under variable lighting


    Beteiligte:
    Kuang-Chih Lee, (Autor:in) / Jeffrey Ho, (Autor:in) / Kriegman, D. (Autor:in)


    Erscheinungsdatum :

    01.01.2001


    Format / Umfang :

    852457 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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    Zhang, L. / Samaras, D. / IEEE | British Library Conference Proceedings | 2003



    Symbolic Factorial Discriminant Analysis for Face Recognition Under Variable Lighting

    Hiremath, P. S. / Prabhakar, C. J. / Visual Information Engineering Network (Institution of Engineering and Technology) | British Library Conference Proceedings | 2006


    Linear subspaces for illumination robust face recognition

    Batur, A.U. / Hayes, M.H.I.I.I. | IEEE | 2001