Skip to main content

Part of the book series: Advances in Pattern Recognition ((ACVPR))

  • 924 Accesses

Abstract

This book has focused on human recognition at a distance by integrating gait and face in video. The research has demonstrated that the proposed video-based fusion system is effective for human identification. The representation of face and gait, where both fuse information from multiple video frames, is promising in real-world applications. The integration of face and gait biometrics will be highly useful in practical applications. Several important problems are addressed in this book. A summary of key contributions in gait-based human recognition, video-based face recognition and fusion of gait and face for individual recognition is given in this chapter.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover 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. Bhanu, B., Govindaraju, V. (eds.): Multibiometrics for Human Identification. Cambridge University Press, Cambridge (2010)

    Google Scholar 

  2. Bhanu, B., Ravishankar, C., Roy-Chowdhury, A., Aghajan, H., Terzopoulos, D. (eds.): Distributed Video Sensor Networks. Springer, Berlin (2010)

    Google Scholar 

  3. Hossain, M.A., Makihara, Y., Wang, J., Yagi, Y.: Clothing-invariant gait identification using part-based clothing categorization and adaptive weight control. Pattern Recognit. 43(6), 2281–2291 (2010)

    Article  Google Scholar 

  4. Nguyen, H., Bhanu, B., Patel, A., Diaz, R.: VideoWeb: design of a wireless camera network for real-time monitoring of activities. In: Third ACM/IEEE International Conference on Distributed Smart Cameras, Como, Italy, 30 August–2 September 2009

    Google Scholar 

  5. Tistarelli, M., Li, S.Z., Chellappa, R.: Handbook of Remote Biometrics: For Surveillance and Security. Springer, Berlin (2009)

    Book  Google Scholar 

  6. Zhang, D., Wang, Y., Bhanu, B.: Age classification based on gait using HMM. In: International Conference on Pattern Recognition, Istanbul, Turkey, August 23–26, 2010

    Google Scholar 

  7. Zhang, D., Wang, Y., Bhanu, B.: Ethnicity classification based on gait using multi-view fusion. In: IEEE Computer Society Workshop on Biometrics, August 18, 2010. Held in Conjunction with IEEE Conference on Computer Vision and Pattern Recognition, San Francisco, CA, June 13–18, 2010

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Bir Bhanu .

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag London Limited

About this chapter

Cite this chapter

Bhanu, B., Han, J. (2010). Conclusions and Future Work. In: Human Recognition at a Distance in Video. Advances in Pattern Recognition. Springer, London. https://doi.org/10.1007/978-0-85729-124-0_12

Download citation

  • DOI: https://doi.org/10.1007/978-0-85729-124-0_12

  • Publisher Name: Springer, London

  • Print ISBN: 978-0-85729-123-3

  • Online ISBN: 978-0-85729-124-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics