Skip to main content
SpringerLink
Log in

Integration of MapReduce with an Interactive Boosting Mechanism for Image Background Subtraction in Cultural Sightseeing

  • Conference paper
  • First Online:
Advances in Web-Based Learning – ICWL 2013 Workshops (ICWL 2013)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8390))

Included in the following conference series:

  • 1056 Accesses

Abstract

Background subtraction is widely used in multimedia applications, such as traffic monitoring, video surveillance, and object tracking. Several methods with different advantages in different applications have been proposed. The advent of cloud computing also has made possible of the combination of various background subtraction techniques and the processing of large amounts of images. In this paper, an integrated algorithm for background subtraction is implemented and analyzed. The proposed AdaBoost algorithm combines weak classifiers: pixel-based background subtraction methods, block-based background subtraction methods, and graph-cut segmentation methods. After training, the program adjusts the weight of each weak classifier. The algorithm is accelerated using Hadoop cloud-computing architecture. By using a MapReduce framework, this system can parallel-processing on multiple servers in order to reduce computing time. When the system completes its task, the user can see the combined results on the screen and then choose the preferred result. The system can obtain user feedback and tune the combination mechanism.

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 EPUB and 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

References

  1. KaewTraKulPong, P., Bowden, R.: An improved adaptive background mixture model for real-time tracking with shadow detection. In: Proceedings of European Workshop Advanced Video Based Surveillance Systems (2001)

    Google Scholar 

  2. Heikkila, M., Pietikainen, M.: A texture-based method for modeling the background and detecting moving objects. IEEE Trans. Pattern Anal. Mach. Intell. 28, 657–662 (2006)

    Article  Google Scholar 

  3. Piccardi, M.: Background subtraction techniques: a review. In: 2004 IEEE International Conference on Systems, Man and Cybernetics, vol. 4, pp. 3099–3104 (2004)

    Google Scholar 

  4. Sun, J., Zhang, W., Tang, X., Shum, H.-Y.: Background cut. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006. LNCS, vol. 3952, pp. 628–641. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  5. Rother, C., Kolmogorov, V., Blake, A.: GrabCut: interactive foreground extraction using iterated graph cuts. ACM Trans. Graph. 23, 309–314 (2004)

    Article  Google Scholar 

  6. Boykov, Y.Y., Jolly, M.P.: Interactive graph cuts for optimal boundary & region segmentation of objects in N-D images. In: Proceedings of Eighth IEEE International Conference on Computer Vision, ICCV 2001, vol. 1, pp. 105–112 (2001)

    Google Scholar 

  7. White, B., Yeh, T., Lin, J., Davis, L.: Web-scale computer vision using MapReduce for multimedia data mining. In: Proceedings of the Tenth International Workshop on Multimedia Data Mining, pp. 1–10 (2010)

    Google Scholar 

  8. Wan, C., Wang, C., Zhang, K.: MRKDSBC: a distributed background modeling algorithm based on MapReduce. In: Wang, J., Yen, G.G., Polycarpou, M.M. (eds.) ISNN 2012, Part I. LNCS, vol. 7367, pp. 668–677. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  9. Almeer, H.M.: Cloud hadoop map reduce for remote sensing image analysis. J. Emerg. Trends Comput. Inf. Sci. 13(4), 637–644 (2012)

    Google Scholar 

  10. Stauffer, C., Grimson, W. E.L.: Adaptive background mixture models for real-time tracking. In: Proceedings of IEEE International Conference on Computer Vision Pattern Recognition, pp. 246–252, Jun 1999

    Google Scholar 

  11. Elgammal, A., Harwood, D., Davis, L.: Non-parametric model for background subtraction. In: Vernon, D. (ed.) ECCV 2000. LNCS, vol. 1843, pp. 751–767. Springer, Heidelberg (2000)

    Chapter  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan

    Sheng-Tzong Cheng, Yin-Jun Chen & Yu-Ting Wang

  2. Department of Information and Communications, Shih Hsin University, Taipei, Taiwan

    Chen-Fei Chen

Authors
  1. Sheng-Tzong Cheng
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yin-Jun Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yu-Ting Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Chen-Fei Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yin-Jun Chen .

Editor information

Editors and Affiliations

  1. Dickson Computer Systems, Kowloon, Hong Kong SAR

    Dickson K. W. Chiu

  2. The University of Hong Kong, Pokfulam, Hong Kong SAR

    Minhong Wang

  3. University of Craiova, Craiova, Romania

    Elvira Popescu

  4. City University of Hong Kong, Hong Kong, Hong Kong SAR

    Qing Li

  5. City University of Hong Kong, Kowloon, Hong Kong SAR

    Rynson Lau

  6. Department of Computer Science and Information Engineering, National Central University, Jhongli City, Taiwan

    Timothy K. Shih

  7. Department of Electrical Engineering, National Cheng Kung University, Taiwan, Taiwan

    Chu-Sing Yang

  8. Digital Systems Centre for Research & Technology Hellas (CERTH), University of Piraeus Dept of Digital Systems, Piraeus, Greece

    Demetrios G. Sampson

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Cheng, ST., Chen, YJ., Wang, YT., Chen, CF. (2015). Integration of MapReduce with an Interactive Boosting Mechanism for Image Background Subtraction in Cultural Sightseeing. In: Chiu, D., et al. Advances in Web-Based Learning – ICWL 2013 Workshops. ICWL 2013. Lecture Notes in Computer Science(), vol 8390. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-46315-4_19

Download citation

  • DOI: https://doi.org/10.1007/978-3-662-46315-4_19

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-46314-7

  • Online ISBN: 978-3-662-46315-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation