Skip to main content
SpringerLink
Log in

Identity Recognition by Incremental Learning

  • Conference paper
  • First Online:
Multimedia and Network Information Systems (MISSI 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 833))

Included in the following conference series:

  • 719 Accesses

Abstract

Face recognition systems nowadays benefit from the improved performance of new classification models combined with the availability of large datasets of face images and the increase of computational power.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Parkhi, O.M., Vedaldi, A., Zisserman, A.: Deep face recognition. In: Proceedings of the British Machine Vision Conference 2015, Swansea, UK (2015)

    Google Scholar 

  2. Scheirer, W.J., de Rezende Rocha, A., Sapkota, A., Boult, T.E.: Toward open set recognition. IEEE Trans. Pattern Anal. Mach. Intell. 35(7), 1757–1772 (2013)

    Google Scholar 

  3. Bendale, A., Boult, T.: Towards open world recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2015)

    Google Scholar 

  4. Korn, F., Muthukrishnan, S.: Influence sets based on reverse nearest neighbor queries. In: Proceedings of the 2000 ACM SIGMOD International Conference on Management of Data, SIGMOD 2000, New York, NY, USA (2000)

    Google Scholar 

  5. Pernici, F., Bartoli, F., Bruni, M., Del Bimbo, A.: Memory based online learning of deep representations from video streams. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2018, Salt Lake City, Utah, USA (2018)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Dipartimento di Ingegneria dell’Informazione, Università degli Studi di Firenze, Via Santa Marta, 3, 50137, Florence, Italy

    Alberto del Bimbo, Federico Pernici, Matteo Bruni & Federico Bartoli

Authors
  1. Alberto del Bimbo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Federico Pernici
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Matteo Bruni
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Federico Bartoli
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Alberto del Bimbo .

Editor information

Editors and Affiliations

  1. Faculty of Computer Science and Management, Wrocław University of Science and Technology, Wrocław, Poland

    Kazimierz Choroś

  2. Faculty of Computer Science and Management, Wrocław University of Science and Technology, Wrocław, Poland

    Marek Kopel

  3. Faculty of Computer Science and Management, Wrocław University of Science and Technology, Wrocław, Poland

    Elżbieta Kukla

  4. Faculty of Computer Science and Management, Wrocław University of Science and Technology, Wrocław, Poland

    Andrzej Siemiński

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

del Bimbo, A., Pernici, F., Bruni, M., Bartoli, F. (2019). Identity Recognition by Incremental Learning. In: Choroś, K., Kopel, M., Kukla, E., Siemiński, A. (eds) Multimedia and Network Information Systems. MISSI 2018. Advances in Intelligent Systems and Computing, vol 833. Springer, Cham. https://doi.org/10.1007/978-3-319-98678-4_1

Download citation

Publish with us

Policies and ethics

Search

Navigation