Skip to main content
SpringerLink
Log in

Person Tracking in UAV Video

  • Conference paper
Multimodal Technologies for Perception of Humans (RT 2007, CLEAR 2007)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 4625))

Abstract

The UAV person tracking task for this evaluation was particularly difficult because of large, complicated, and low-quality videos, with only small images of people. We found that our best results were obtained using a combination of intensity thresholding (for IR imagery), motion compensation, interest-point detection and correspondence, and pattern classification. This can be considered a preliminary exploration into an extremely challenging problem.

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 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Ali, S., Shah, M.: Cocoa - tracking in aerial imagery. In: SPIE Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications, Orlando (2006)

    Google Scholar 

  2. Javed, O., Shah, M.: Tracking and object classification for automated surveillance. In: The Seventh European Conference on Computer Vision, Denmark (2002)

    Google Scholar 

  3. Sheikh, Y., Zhai, Y., Shah, M.: An accumulative framework for alignment of an image sequence. In: Proceedings of Asian Conference on Computer Vision (2004)

    Google Scholar 

  4. Shafique, K., Shah, M.: A noniterative greedy algorithm for multiframe point correspondence. In: IEEE Trans. Pattern Anal. Mach. Intell. (2005)

    Google Scholar 

  5. Ahmed, J., Jafri, M.N., Shah, M., Akbar, M.: Real-time edge-enhanced dynamic correlation and predictive open-loop car-following control for robust tracking. Machine Vision and Applications Journal, Manuscript submission ID MVA-May-06-0110 (accepted, 2007)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Computer Vision Lab at University of Central Florida,  

    Andrew Miller, Pavel Babenko, Min Hu & Mubarak Shah

Authors
  1. Andrew Miller
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Pavel Babenko
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Min Hu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Mubarak Shah
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Rainer Stiefelhagen Rachel Bowers Jonathan Fiscus

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Miller, A., Babenko, P., Hu, M., Shah, M. (2008). Person Tracking in UAV Video. In: Stiefelhagen, R., Bowers, R., Fiscus, J. (eds) Multimodal Technologies for Perception of Humans. RT CLEAR 2007 2007. Lecture Notes in Computer Science, vol 4625. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68585-2_19

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-68585-2_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-68584-5

  • Online ISBN: 978-3-540-68585-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation