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Multi-person Tracking in Meetings: A Comparative Study

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4299))

Abstract

In this paper, we present the findings of the Augmented Multiparty Interaction (AMI) project investigation on the localization and tracking of 2D head positions in meetings. The focus of the study was to test and evaluate various multi-person tracking methods developed in the project using a standardized data set and evaluation methodology.

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References

  1. Cootes, T., Taylor, C.: Statistical models of appearance for computer vision (2004)

    Google Scholar 

  2. Cootes, T., Edwards, G., Taylor, C.: A comparative evaluation of active appearance model algorithms. In: British Machine Vision Conference, Southampton, UK (September 1998)

    Google Scholar 

  3. Gatica-Perez, D.: Annotation Procedure for WP4-locate. In: AMI Internal Document, Martigny, Switzerland (October 2004)

    Google Scholar 

  4. Hradis, M., Juranek, R.: Real-time Tracking of Participants in Meeting Video. In: Proceedings of CESCG, Wien (2006)

    Google Scholar 

  5. Isard, M., Blake, A.: Condensation – conditional density propagation for visual tracking. International Journal of Computer Vision 29(1), 5–28 (1998)

    Article  Google Scholar 

  6. Isard, M., Blake, A.: A Mixed-State CONDENSATION Tracker with Automatic Model-Switching. In: International Conference on Computer Vision (ICCV) (1998)

    Google Scholar 

  7. Kasture, R., et al.: Performance Evaluation Protocol for Face, Person, and Vehicle Detection & Tracking Analysis and Content Extraction (VACE-II), ARDA Technical Report, Tampa, FL (2006)

    Google Scholar 

  8. Kölsch, M., Turk, M.: Fast 2D Hand Tracking With Flocks and Multi Cue Integration, Department of Computer Science, University of California (2005)

    Google Scholar 

  9. Kruger, V.: Wavelet Networks for Object Representation. thesis dissertation, Technischen Fakultat, Christian-Albrechts-Universitat zu Kiel (2000)

    Google Scholar 

  10. Potucek, I., Sumec, S., Spanel, M.: Participant activity detection by hands and face movement tracking in the meeting room. In: Computer Graphics International (CGI), Los Alamitos (2004)

    Google Scholar 

  11. Van Rijsbergen, C.J.: Information Retrieval. Butterworth-Heinemann, Newton (1979)

    Google Scholar 

  12. Smith, K., Ba, S., Odobez, J.M., Gatica-Perez, D.: Multi-Person Wander-Visual-Focus-of-Attention Tracking, IDIAP-RR-05-80 (November 2005)

    Google Scholar 

  13. Smith, K., Ba, S., Odobez, J.M., Gatica-Perez, D.: Evaluating Multi-Object Tracking. In: CVPR Workshop on Empirical Evaluation Methods in Computer Vision (EEMCV), San Diego, CA (June 2005)

    Google Scholar 

  14. Viola, J., Jones, M.: Robust Real-time Object Detection, Technical Report 2001/01, Compaq CRL (February 2001)

    Google Scholar 

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© 2006 Springer-Verlag Berlin Heidelberg

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Smith, K., Schreiber, S., Potúcek, I., Beran, V., Rigoll, G., Gatica-Perez, D. (2006). Multi-person Tracking in Meetings: A Comparative Study. In: Renals, S., Bengio, S., Fiscus, J.G. (eds) Machine Learning for Multimodal Interaction. MLMI 2006. Lecture Notes in Computer Science, vol 4299. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11965152_8

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  • DOI: https://doi.org/10.1007/11965152_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-69267-6

  • Online ISBN: 978-3-540-69268-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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