%Aigaion2 BibTeX export from Idiap Publications
%Saturday 21 December 2024 06:03:43 PM

@INPROCEEDINGS{Korchagin_ICASSP_2010,
         author = {Korchagin, Danil and Garner, Philip N. and Dines, John},
       keywords = {pattern matching, reliability estimation, time synchronization, time-frequency analysis},
       projects = {Idiap, TA2},
          month = {3},
          title = {Automatic Temporal Alignment of AV Data with Confidence Estimation},
      booktitle = {Proceedings IEEE International Conference on Acoustics, Speech and Signal Processing},
           year = {2010},
       location = {Dallas, USA},
        address = {P.O. Box 592, CH-1920 Martigny, Switzerland},
       crossref = {Korchagin_Idiap-RR-40-2009},
       abstract = {In this paper, we propose a new approach for the automatic audio-based temporal alignment with confidence estimation of audio-visual data, recorded by different cameras, camcorders or mobile phones during social events. All recorded data is temporally aligned based on ASR-related features with a common master track, recorded by a reference camera, and the corresponding confidence of alignment is estimated. The core of the algorithm is based on perceptual time-frequency analysis with a precision of 10 ms. The results show correct alignment in 99\% of cases for a real life dataset and surpass the performance of cross correlation while keeping lower system requirements.},
            pdf = {https://publications.idiap.ch/attachments/papers/2009/Korchagin_ICASSP_2010.pdf}
}



crossreferenced publications: 
@TECHREPORT{Korchagin_Idiap-RR-40-2009,
         author = {Korchagin, Danil and Garner, Philip N. and Dines, John},
       keywords = {pattern matching, reliability estimation, time synchronisation, time-frequency analysis},
       projects = {Idiap, TA2},
          month = {12},
          title = {Automatic Temporal Alignment of AV Data with Confidence Estimation},
           type = {Idiap-RR},
         number = {Idiap-RR-40-2009},
           year = {2009},
    institution = {Idiap},
        address = {CH-1920 Martigny, Switzerland},
       abstract = {In this paper, we propose a new approach for the automatic audio-based temporal alignment with confidence estimation of audio-visual data, recorded by different cameras, camcorders or mobile phones during social events. All recorded data is temporally aligned based on ASR-related features with a common master track, recorded by a reference camera, and the corresponding confidence of alignment is estimated. The core of the algorithm is based on perceptual time-frequency analysis with a precision of 10 ms. The results show correct alignment in 99\% of cases for a real life dataset and surpass the performance of cross correlation while keeping lower system requirements.},
            pdf = {https://publications.idiap.ch/attachments/reports/2009/Korchagin_Idiap-RR-40-2009.pdf}
}