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International Visual Informatics Conference

IVIC 2019: Advances in Visual Informatics pp 227–236Cite as

A Comprehensive Review Towards Appropriate Feature Selection for Moving Object Detection Using Aerial Images

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 11870))

Abstract

Efficient feature extraction for moving object using aerial images is still an unsolved issue in computer vision, image processing and pattern recognition research domains. Aerial types of images contain various environmental constraints due to capture frames from various altitudes level, i.e. illumination, shadows, occlusion. For this reason, appropriate feature selection for those types of images needs more attention by the researchers to improve detection rate with fast and computationally less complex features extraction method. This research performed comprehensive review with critical analysis for using various features with various methods for moving object detection using aerial images. In this context, three aspects for critical analysis of using various features are identified followed by challenges of using various features. After that, existing methods with advantages and barriers are comprehensively described with various constraints claimed by the previous research. Next, justification for the need of new feature selection is elaborated for optimum detection performance. Later, adequate validation matrics are illustrated to evaluate various features based moving object detection using aerial images performed in the previous research. The overall review performed in this paper have been comprehensively studied and expected to contribute significantly in computer vision, image processing pattern recognition research field.

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References

  1. Yang, Y., Liu, F., Wang, P., Luo, P., Liu, X.: Vehicle detection methods from an unmanned aerial vehicle platform. In: 2012 IEEE International Conference on Vehicular Electronics and Safety (ICVES 2012), pp. 411–415. IEEE (2012)

    Google Scholar 

  2. Wang, S.: Vehicle detection on aerial images by extracting corner features for rotational invariant shape matching. In: 2011 IEEE 11th International Conference on Computer and Information Technology, pp. 171–175. IEEE (2011)

    Google Scholar 

  3. Ibrahim, A.W.N., Ching, P.W., Seet, G.G., Lau, W.M., Czajewski, W.: Moving objects detection and tracking framework for UAV-based surveillance. In: 2010 Fourth Pacific-Rim Symposium on Image and Video Technology, pp. 456–461. IEEE (2010)

    Google Scholar 

  4. Saif, A.S., Prabuwono, A.S., Mahayuddin, Z.R., Mantoro, T.: Vision-based human face recognition using extended principal component analysis. Int. J. Mob. Comput. Multimedia Commun. (IJMCMC) 5, 82–94 (2013)

    Article  Google Scholar 

  5. Cheng, H.-Y., Weng, C.-C., Chen, Y.-Y.: Vehicle detection in aerial surveillance using dynamic Bayesian networks. IEEE Trans. Image Process. 21, 2152–2159 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  6. Pollard, T., Antone, M.: Detecting and tracking all moving objects in wide-area aerial video. In: 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, pp. 15–22. IEEE (2012)

    Google Scholar 

  7. Cheraghi, S.A., Sheikh, U.U.: Moving object detection using image registration for a moving camera platform. In: 2012 IEEE International Conference on Control System, Computing and Engineering, pp. 355–359. IEEE (2012)

    Google Scholar 

  8. Luo, P., Liu, F., Liu, X., Yang, Y.: Stationary vehicle detection in aerial surveillance with a UAV. In: 2012 8th International Conference on Information Science and Digital Content Technology (ICIDT2012), pp. 567–570. IEEE (2012)

    Google Scholar 

  9. Moranduzzo, T., Melgani, F.: A SIFT-SVM method for detecting cars in UAV images. In: 2012 IEEE International Geoscience and Remote Sensing Symposium, pp. 6868–6871. IEEE, (2012)

    Google Scholar 

  10. Chen, L., Jiang, Z., Yang, J., Ma, Y.: A coarse-to-fine approach for vehicles detection from aerial images. In: 2012 International Conference on Computer Vision in Remote Sensing, pp. 221–225. IEEE (2012)

    Google Scholar 

  11. Zheng, Z., Wang, X., Zhou, G., Jiang, L.: Vehicle detection based on morphology from highway aerial images. In: 2012 IEEE International Geoscience and Remote Sensing Symposium, pp. 5997–6000. IEEE (2012)

    Google Scholar 

  12. Kembhavi, A., Harwood, D., Davis, L.S.: Vehicle detection using partial least squares. IEEE Trans. Pattern Anal. Mach. Intell. 33, 1250–1265 (2011)

    Article  Google Scholar 

  13. Gleason, J., Nefian, A.V., Bouyssounousse, X., Fong, T., Bebis, G.: Vehicle detection from aerial imagery. In: 2011 IEEE International Conference on Robotics and Automation, pp. 2065–2070. IEEE (2011)

    Google Scholar 

  14. Wang, L., Zhao, H., Guo, S., Mai, Y., Liu, S.: The adaptive compensation algorithm for small UAV image stabilization. In: 2012 IEEE International Geoscience and Remote Sensing Symposium, pp. 4391–4394. IEEE (2012)

    Google Scholar 

  15. Bhuvaneswari, K., Rauf, H.A.: Edgelet based human detection and tracking by combined segmentation and soft decision. In: 2009 International Conference on Control, Automation, Communication and Energy Conservation, pp. 1–6. IEEE (2009)

    Google Scholar 

  16. Mofaddel, M.A., Abd-Elhafiez, W.M.: Fast and accurate approaches for image and moving object segmentation. In: The 2011 International Conference on Computer Engineering & Systems, pp. 252–259. IEEE (2011)

    Google Scholar 

  17. Huang, C.-H., Wu, Y.-T., Kao, J.-H., Shih, M.-Yu., Chou, C.-C.: A hybrid moving object detection method for aerial images. In: Qiu, G., Lam, K.M., Kiya, H., Xue, X.-Y., Kuo, C.-C.Jay, Lew, M.S. (eds.) PCM 2010. LNCS, vol. 6297, pp. 357–368. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-15702-8_33

    Chapter  Google Scholar 

  18. Gaszczak, A., Breckon, T.P., Han, J.: Real-time people and vehicle detection from UAV imagery. In: SPIE (2011)

    Google Scholar 

  19. Qian, Y., Medioni, G.: Motion pattern interpretation and detection for tracking moving vehicles in airborne video. In: 2009 IEEE Conference on Computer Vision and Pattern Recognition, pp. 2671–2678 (2009)

    Google Scholar 

  20. Breckon, T.P., Barnes, S.E., Eichner, M.L., Wahren, K.: Autonomous real-time vehicle detection from a medium-level UAV. In: 24th International Conference on Unmanned Air Vehicle Systems (2009)

    Google Scholar 

  21. Teutsch, M., Krüger, W.: Spatio-temporal fusion of object segmentation approaches for moving distant targets. In: 2012 15th International Conference on Information Fusion, pp. 1988–1995 (2012)

    Google Scholar 

  22. Oreifej, O., Mehran, R., Shah, M.: Human identity recognition in aerial images. In: 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 709–716. IEEE (2010)

    Google Scholar 

  23. Jiang, Z., Ding, W., Li, H.: Aerial video image object detection and tracing based on motion vector compensation and statistic analysis. In: 2009 Asia Pacific Conference on Postgraduate Research in Microelectronics & Electronics (PrimeAsia), pp. 302–305. IEEE (2009)

    Google Scholar 

  24. Saif, A.S., Prabuwono, A.S., Mahayuddin, Z.R.: Motion analysis for moving object detection from UAV aerial images: A review. In: 2014 International Conference on Informatics, Electronics & Vision (ICIEV), pp. 1–6. IEEE (2014)

    Google Scholar 

  25. Saif, A.F.M.S., Prabuwono, A.S., Mahayuddin, Z.R.: Real time vision based object detection from UAV aerial images: a conceptual framework. In: Omar, K., et al. (eds.) FIRA 2013. CCIS, vol. 376, pp. 265–274. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-40409-2_23

    Chapter  Google Scholar 

  26. Zebbara, K., Ansari, M.E., Mazoul, A., Oudani, H.: A fast road obstacle detection using association and symmetry recognition. In: 2019 International Conference on Wireless Technologies, Embedded and Intelligent Systems (WITS) (2019)

    Google Scholar 

  27. Vasavi, S., Shaik, A.F.: Moving object classification under illumination changes using binary descriptors. In: Optoelectronics in Machine Vision-Based Theories and Applications, pp. 188–232. IGI Global (2019)

    Google Scholar 

  28. Wang, Y., et al.: Detection and classification of moving vehicle from video using multiple spatio-temporal features. IEEE Access 7, 80287–80299 (2019)

    Article  Google Scholar 

  29. Saif, A.S., Prabuwono, A.S., Mahayuddin, Z.R.: Moment feature based fast feature extraction algorithm for moving object detection using aerial images. PloS one 10, e0126212 (2015)

    Google Scholar 

  30. Saif, A., Prabuwono, A.S., Mahayuddin, Z.R.: Moving object detection using dynamic motion modelling from UAV aerial images. Sci. World J. 2014 (2014)

    Google Scholar 

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Acknowledgements

The authors would like to thank Universiti Kebangsaan Malaysia for providing financial support under the GERAN GALAKAN PENYELIDIKAN research grant, GGP-2017-030.

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Authors and Affiliations

  1. Faculty of Information Science and Technology, University Kebangsaan Malaysia, Bangi, Selangor, Malaysia

    Zainal Rasyid Mahayuddin

  2. Faculty of Science and Technology, American International University–Bangladesh, Dhaka, Bangladesh

    A. F. M. Saifuddin Saif

Authors
  1. Zainal Rasyid Mahayuddin
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  2. A. F. M. Saifuddin Saif
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Corresponding author

Correspondence to A. F. M. Saifuddin Saif .

Editor information

Editors and Affiliations

  1. Universiti Kebangsaan Malaysia, Bangi, Malaysia

    Halimah Badioze Zaman

  2. Dublin City University, Dublin, Ireland

    Alan F. Smeaton

  3. National Central University, Taoyuan City, Taiwan

    Timothy K. Shih

  4. Carlos III University of Madrid, Madrid, Spain

    Sergio Velastin

  5. Toyo University, Tokyo, Japan

    Tada Terutoshi

  6. Universiti Kebangsaan Malaysia, Bangi, Malaysia

    Nazlena Mohamad Ali

  7. Universiti Kebangsaan Malaysia, Bangi, Malaysia

    Mohammad Nazir Ahmad

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© 2019 Springer Nature Switzerland AG

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Mahayuddin, Z.R., Saif, A.F.M.S. (2019). A Comprehensive Review Towards Appropriate Feature Selection for Moving Object Detection Using Aerial Images. In: Badioze Zaman, H., et al. Advances in Visual Informatics. IVIC 2019. Lecture Notes in Computer Science(), vol 11870. Springer, Cham. https://doi.org/10.1007/978-3-030-34032-2_21

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  • DOI: https://doi.org/10.1007/978-3-030-34032-2_21

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-34031-5

  • Online ISBN: 978-3-030-34032-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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