%Aigaion2 BibTeX export from Idiap Publications
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         author = {Sanderson, Conrad and Paliwal, Kuldip K.},
       projects = {Idiap},
          month = {4},
          title = {Noise {R}esistant Audio-{V}isual {V}erification via {S}tructural {C}onstraints},
      booktitle = {{P}roceedings of the 2003 {IEEE} International {C}onference on Acoustics, {S}peech, and {S}ignal {P}rocessing ({ICASSP}-03)},
           year = {2003},
        address = {Hong Kong},
       crossref = {sanders-rr-02-33},

crossreferenced publications: 
         author = {Sanderson, Conrad and Paliwal, Kuldip K.},
       projects = {Idiap},
          month = {9},
          title = {{I}nformation {F}usion and {P}erson {V}erification Using {S}peech & {F}ace Information},
           type = {Idiap-RR},
         number = {Idiap-RR-33-2002},
           year = {2002},
    institution = {IDIAP},
       abstract = {This report provides an overview of important concepts in the field of information fusion, followed by a review of literature pertaining to audio-visual person identification & verification. Several recent adaptive and non-adaptive techniques for reaching the verification decision (i.e., to accept or reject the claimant,',','),
 based on audio and visual information, are evaluated in clean and noisy conditions on a common database using a text-independent setup. It is shown that in clean conditions all the non-adaptive approaches provide similar performance; in noisy conditions they exhibit deterioration in their performance. It is also shown that current adaptive approaches are either inadequate or utilize restrictive assumptions. A new category of classifiers is then introduced, where the decision surface is fixed but constructed to take into account the effects of noisy conditions, providing a good trade-off between performance in clean and noisy conditions.},
            pdf = {https://publications.idiap.ch/attachments/reports/2002/rr02-33.pdf},
     postscript = {ftp://ftp.idiap.ch/pub/reports/2002/rr02-33.ps.gz},