Skip to main content

Matlab GUI Application for Moving Object Detection and Tracking

  • Conference paper
  • First Online:

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 801))

Abstract

In this paper a novel tool for moving object detection and tracking is presented. The main contribution of the proposed application is the achievement of a simple and intuitive graphic interface during the extraction the silhouette of targets by means of a new algorithm. This proposed algorithm which combined frame difference method, background subtraction method, Laplace filter and Canny edge detector together can realize a way to achieve sparse detection fast. Some modular architecture in this Graphical User Interface has been developed in order to enhance the user’s experience. The experiment was tested by using sequence images from the MULTIVITION dataset, and experimental results showed that our proposed method has more validity and flexibility to get the desired result than conventional algorithm.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   169.99
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

Learn about institutional subscriptions

References

  1. Milan, A., Rezatofighi, S.H., Dick, A.R., Reid, I.D., Schindler, K.: Online multi-target tracking using recurrent neural networks. In: AAAI, pp. 4225–4232 (2017)

    Google Scholar 

  2. Shotton, J., Blake, A., Cipolla, R.: Contour-based learning for object detection. In: Tenth IEEE International Conference in Computer Vision, vol. 1, pp. 503–510 (2005)

    Google Scholar 

  3. Zhong, Z., Zhang, B., Lu, G., Zhao, Y., Xu, Y.: An adaptive background modeling method for foreground segmentation. IEEE Trans. Intell. Transp. Syst. 18(5), 1109–1121 (2017)

    Article  Google Scholar 

  4. Sulaiman, S., Hussain, A., Tahir, N.M., Samad, S.A.: Graphical user interface (GUI) development for object tracking system in video sequences. World Appl. Sci. J. 4(2), 244–249 (2008)

    Google Scholar 

  5. Kumar, G.N.: Moving Object Detection and Tracking Using MATLAB GUI with ARDUINO

    Google Scholar 

  6. Fernandez-Sanchez, E.J., Rubio, L., Diaz, J., Ros, E.: Background subtraction model based on color and depth cues. Mach. Vis. Appl. 25(5), 1211–1225 (2014)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Beibei Cui .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Cui, B., Créput, JC. (2019). Matlab GUI Application for Moving Object Detection and Tracking. In: Rodríguez, S., et al. Distributed Computing and Artificial Intelligence, Special Sessions, 15th International Conference. DCAI 2018. Advances in Intelligent Systems and Computing, vol 801. Springer, Cham. https://doi.org/10.1007/978-3-319-99608-0_44

Download citation

Publish with us

Policies and ethics