Skip to main content
SpringerLink
Log in

Fast Pedestrian Detection Using Color Information

  • Conference paper
Intelligence and Security Informatics (ISI 2006)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 3975))

Included in the following conference series:

Abstract

In a pedestrian detection system, the application of color information can increase the detection rate; however, the detection speed will be slowed down a lot. This paper presents a fast pedestrian detection method using color information. It firstly scans a pair of sequential gray-scale frames to select candidates using both appearance and motion features; and then uses information of each color channel (RGB) to do a further confirmation with support vector machine based classifiers. Compared with pedestrian detection systems that only use gray-scale information, the system using our method has almost the same detection speed; at the same time, it also gets a better detection rate and false-positive rate. The experiment in a pedestrian detection system with a single optical camera proves the effectiveness of our method.

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 84.99
Price excludes VAT (USA)
  • Available as 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

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. Gavrila, D.M.: Pedestrian detection from a moving vehicle. In: Vernon, D. (ed.) ECCV 2000. LNCS, vol. 1843, pp. 37–49. Springer, Heidelberg (2000)

    Chapter  Google Scholar 

  2. Viola, P., Jones, M., Snow, D.: Detecting Pedestrians Using Patterns of Motion and Appearance. In: International Conference on Computer Vision (ICCV), vol. 2, pp. 734–741 (2003)

    Google Scholar 

  3. Papageorgiou, C., Poggio, T.: Trainable pedestrian detection. In: International Conference on Image Processing, vol. 4, pp. 35–39 (1999)

    Google Scholar 

  4. Joachims, T.: Making large-scale SVM learning practical. In: Schölkopf, B., Burges, C.J.C., Smola, A.J. (eds.) Advances in Kernel Methods – Support Vector Learning. MIT Press, Cambridge (1998)

    Google Scholar 

  5. Viola, P., Jones, M.: Robust Real-Time Face Detection. International Journal of Computer Vision 57, 137–154 (2004)

    Article  Google Scholar 

  6. Zhang, X.G.: Introduction to statistical learning theory and support vector machines. Acta Automatica Sinica 26, 32–42 (2000)

    MathSciNet  Google Scholar 

  7. Xu, F., Liu, X., Fujimura, K.: Pedestrian Detection and Tracking with Night Vision. IEEE Transaction on Intelligent Transportation Systems 6, 63–71 (2005)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science and Technology, University of Science and Technology of China, Hefei, 230026, P.R. China

    Y. W. Xu & X. B. Cao

  2. Anhui Province Key Laboratory of Software in Computing and Communication, Hefei, 230026, P.R. China

    Y. W. Xu & X. B. Cao

  3. Institute of Automation, Chinese Academy of Sciences, Beijing, 10080, P.R. China

    H. Qiao & F. Y. Wang

Authors
  1. Y. W. Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. X. B. Cao
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. H. Qiao
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. F. Y. Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. School of Information and Computer Science, University of California, Irvine

    Sharad Mehrotra

  2. MIS Department, University of Arizona, 85721, Tucson, AZ, USA

    Daniel D. Zeng

  3. Department of Management Information Systems, Eller College of Management, The University of Arizona, 85721, AZ, USA

    Hsinchun Chen

  4. University of Texas at Dallas,  

    Bhavani Thuraisingham

  5. Chinese Academy of Sciences, 100190, Beijing, China

    Fei-Yue Wang

Rights and permissions

Reprints and permissions

Copyright information

© 2006 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Xu, Y.W., Cao, X.B., Qiao, H., Wang, F.Y. (2006). Fast Pedestrian Detection Using Color Information. In: Mehrotra, S., Zeng, D.D., Chen, H., Thuraisingham, B., Wang, FY. (eds) Intelligence and Security Informatics. ISI 2006. Lecture Notes in Computer Science, vol 3975. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11760146_68

Download citation

  • DOI: https://doi.org/10.1007/11760146_68

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34478-0

  • Online ISBN: 978-3-540-34479-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation