%Aigaion2 BibTeX export from Idiap Publications
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@TECHREPORT{Korchagin_Idiap-RR-42-2010,
         author = {Korchagin, Danil},
       projects = {Idiap, TA2},
          month = {12},
          title = {Automatic Time Skew Detection and Correction},
           type = {Idiap-RR},
         number = {Idiap-RR-42-2010},
           year = {2010},
    institution = {Idiap},
        address = {Martigny, Switzerland},
       crossref = {Korchagin_ICSAP_2011},
       abstract = {In this paper, we propose a new approach for the automatic time skew detection and correction for multisource audiovisual data, recorded by different cameras/recorders during the same event. All recorded data are successfully tested for potential time skew problem and corrected based on ASR-related features. The core of the algorithm is based on perceptual time-quefrency analysis with a precision of 10 ms. The results show correct time skew detection and elimination in 100\% of cases for a real life dataset of 32 broken sessions and surpass the performance of fast cross correlation while keeping lower system requirements.},
            pdf = {https://publications.idiap.ch/attachments/reports/2010/Korchagin_Idiap-RR-42-2010.pdf}
}



crossreferenced publications: 
@INPROCEEDINGS{Korchagin_ICSAP_2011,
         author = {Korchagin, Danil},
       keywords = {pattern matching, time synchronisation, time-quefrency analysis},
       projects = {Idiap, TA2},
          month = {2},
          title = {Automatic Time Skew Detection and Correction},
      booktitle = {Proceedings International Conference on Signal Acquisition and Processing},
           year = {2011},
       location = {Singapore},
        address = {Martigny, Switzerland},
       crossref = {Korchagin_Idiap-RR-42-2010},
       abstract = {In this paper, we propose a new approach for the automatic time skew detection and correction for multisource audiovisual data, recorded by different cameras/recorders during the same event. All recorded data are successfully tested for potential time skew problem and corrected based on ASR-related features. The core of the algorithm is based on perceptual time-quefrency analysis with a precision of 10 ms. The results show correct time skew detection and elimination in 100\% of cases for a real life dataset of 32 broken sessions and surpass the performance of fast cross correlation while keeping lower system requirements.},
            pdf = {https://publications.idiap.ch/attachments/papers/2010/Korchagin_ICSAP_2011.pdf}
}