%Aigaion2 BibTeX export from Idiap Publications
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         author = {Cardinaux, Fabien},
       projects = {Idiap},
          title = {{L}ocal {F}eatures and {1D-HMMs} for {F}ast and {R}obust {F}ace Authentication},
           type = {Idiap-RR},
         number = {Idiap-RR-17-2005},
           year = {2005},
    institution = {IDIAP},
       abstract = {It has been previously demonstrated that systems based on Hidden Markov Models (HMMs) are suitable for face recognition. The proposed approaches in the literature are either HMMs with one-dimensional (1D-HMMs) or two-dimensional (2D-HMMs) topology. Both have shown some serious drawbacks. The 1D-HMM approaches typically use a whole row (or column) of an image as observation vector and by consequence do not allow horizontal (or vertical) alignment. 2D-HMM approaches present some implementation issues because of the computational cost. In this paper, we propose a 1D-HMM approach which allow the use of local features and we will demonstate the accuracy of this approach on the so-called BANCA database.},
            pdf = {https://publications.idiap.ch/attachments/reports/2005/rr05-17.pdf},
     postscript = {ftp://ftp.idiap.ch/pub/reports/2005/rr05-17.ps.gz},