Skip to main content

Pedestrian Traffic Distribution Analysis Using Face Recognition Technology

  • Conference paper
Activities of Transport Telematics (TST 2013)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 395))

Included in the following conference series:

Abstract

Pedestrian traffic distribution analysis in big public transport interchanges is aimed at improving transfer conditions, schedule optimization and route planning. Traditional survey of people flow is based on counting and interviewing of travellers. In the article, a new method of transport interchange analysis using image processing method is presented. In November 2009, Bemowo-Ratusz interchange in Warsaw has been subjected to detailed examination. The study was associated with the planned redevelopment. In parallel with the survey based on image processing methods, the traditional interview-based survey has been conducted in order to compare the results. Passenger transfer matrices obtained from optical analysis and traditional survey show good correlation. This proves the effectiveness and shows potential of image analysis methods for this kind of application.

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 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. Kukharev, G., Kuzminski, A., Nowosielski, A.: Structure and Characteristics of Face Recognition Systems. Computing, Multimedia and Intelligent Techniques. Special issue on Live Biometrics and Security 1(1), 111–124 (2005)

    Google Scholar 

  2. Yang, M., Kriegman, D., Ahuja, N.: Detecting Faces in Images: A Survey. IEEE Transactions on Pattern Analysis and Machine Intelligence 24(1), 34–58 (2002)

    Article  Google Scholar 

  3. Viola, P., Jones, M.J.: Robust Real-Time Face Detection. International Journal of Computer Vision 57(2), 137–154 (2004)

    Article  Google Scholar 

  4. Zhang, X., Gao, Y.: Face recognition across pose: A review. Pattern Recognition 42, 2876–2896 (2009)

    Article  Google Scholar 

  5. Kukharev, G., Forczmański, P., Nowosielski, A.: Wykorzystanie prostych ekstraktorów cech obrazu w programowo-sprzętowych systemach biometrycznych (Simple facial features extractors utilization in hardware-software biometric systems). Pomiary Automatyka Kontrola 7-bis206, 77–79 (2006)

    Google Scholar 

  6. Kukharev, G., Mikłasz, M., Sabuda, R., Kawka, G.: Metoda ekstrakcji cech orientowanych na sprzętową realizację w zadaniach rozpoznawania obrazów. Pomiary Automatyka Kontrola (8), 563–565 (2009)

    Google Scholar 

  7. Olszewski, P., Krukowski, P.: Quantitative assessment of public transport interchanges. In: 40th European Transport Conference, Glasgow (2012)

    Google Scholar 

  8. Zhao, W., Chellappa, R., Phillips, P.J., Rosenfeld, A.: Face Recognition: A Literature Survey. ACM Computing Surveys 35(4), 399–458 (2003)

    Article  Google Scholar 

  9. Bowyer, K.W., Chang, K., Flynn, P.: A survey of approaches and challenges in 3D and multi-modal 3D + 2D face recognition. Computer Vision and Image Understanding 101(1), 1–15 (2006)

    Article  Google Scholar 

  10. Kong, S.G., Heo, J., Abidi, B.R., Paik, J., Abidi, A.M.: Recent advances in visual and infrared face recognition - a review. Computer Vision and Image Understanding 97(1), 103–135 (2005)

    Article  Google Scholar 

  11. Tan, X., Chen, S., Zhou, Z.-H., Zhang, F.: Face recognition from a single image per person: A survey. Pattern Recognition 39, 1725–1745 (2006)

    Article  MATH  Google Scholar 

  12. http://www.neurotechnology.com/verilook.html (date of access: July 26, 2013)

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Mikłasz, M., Olszewski, P., Nowosielski, A., Kawka, G. (2013). Pedestrian Traffic Distribution Analysis Using Face Recognition Technology. In: Mikulski, J. (eds) Activities of Transport Telematics. TST 2013. Communications in Computer and Information Science, vol 395. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41647-7_37

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-41647-7_37

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-41646-0

  • Online ISBN: 978-3-642-41647-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics