Advertisement

Adaptive Motion Pattern Analysis for Machine Vision Based Moving Detection from UAV Aerial Images

  • A. F. M. Saifuddin Saif
  • Anton Satria Prabuwono
  • Zainal Rasyid Mahayuddin
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8237)

Abstract

In order to detect moving object from UAV aerial images motion analysis has started to get attention in recent years where motion of the objects along with moving camera needs to be estimated and compensated by using detection algorithm. Moving object detection from UAV aerial images based on motion analysis involves modeling the pixel value changes over time. Moving object detection with moving cameras from UAV aerial images is still an unsolved issue due to not considering irregular motion of camera and improper estimation of noise, object motion changes and finally unfixed moving object direction. This paper presents a low complexity based motion analysis framework for moving object detection along with camera motion estimation by considering motion change of moving object and unfixed moving object direction. Based on the experimental results it is expected that proposed motion vector estimation performs well for both invariant motion and invariant moving object direction.

Keywords

machine vision motion analysis moving object detection 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    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 (CVPRW), pp. 15–22 (2012)Google Scholar
  2. 2.
    Zezhong, Z., Xiaoting, W., Guoqing, Z., Ling, J.: Vehicle detection based on morphology from highway aerial images. In: 2012 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), pp. 5997–6000 (2012)Google Scholar
  3. 3.
    Moranduzzo, T., Melgani, F.: A SIFT-SVM method for detecting cars in UAV images. In: 2012 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), pp. 6868–6871 (2012)Google Scholar
  4. 4.
    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 (ICCSCE), pp. 355–359 (2012)Google Scholar
  5. 5.
    Pingting, L., Fuqiang, L., Xiaofeng, L., Yingqian, Y.: Stationary vehicle detection in aerial surveillance with a UAV. In: 2012 8th International Conference on Information Science and Digital Content Technology (ICIDT), pp. 567–570 (2012)Google Scholar
  6. 6.
    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 (ICRA), pp. 2065–2070 (2011)Google Scholar
  7. 7.
    Gąszczak, A., Breckon, T.P., Han, J.: Real-time people and vehicle detection from UAV imagery (2011)Google Scholar
  8. 8.
    Sheng, W.: 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 (CIT), pp. 171–175 (2011)Google Scholar
  9. 9.
    Oreifej, O., Mehran, R., Shah, M.: Human identity recognition in aerial images, pp. 709–716 (2010)Google Scholar
  10. 10.
    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, pp. 29.21-29.29 (2009)Google Scholar
  11. 11.
    Qian, Y., Medioni, G.: Motion pattern interpretation and detection for tracking moving vehicles in airborne video. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2009, pp. 2671–2678 (2009)Google Scholar
  12. 12.
    Ibrahim, A.W.N., Pang Wee, C., Seet, G.L.G., Lau, W.S.M., Czajewski, W.: Moving Objects Detection and Tracking Framework for UAV-based Surveillance. In: 2010 Fourth Pacific-Rim Symposium on Image and Video Technology (PSIVT), pp. 456–461 (2010)Google Scholar
  13. 13.
    Jiang, Z., Ding, W., Li, H.: Aerial video image object detection and tracing based on motion vector compensation and statistic analysis. In: Asia Pacific Conference on Postgraduate Research in Microelectronics & Electronics, PrimeAsia 2009, pp. 302–305 (2009)Google Scholar
  14. 14.
    Mahmoudi, M., Sapiro, G.: Fast image and video denoising via nonlocal means of similar neighborhoods. IEEE Signal Processing Letters 12, 839–842 (2005)CrossRefGoogle Scholar
  15. 15.
    Jaakkola, T.S., Jordan, M.I.: Bayesian parameter estimation via variational methods. Statistics and Computing 10, 25–37 (2000)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • A. F. M. Saifuddin Saif
    • 1
  • Anton Satria Prabuwono
    • 1
  • Zainal Rasyid Mahayuddin
    • 1
  1. 1.Faculty of Information Science and TechnologyUniversity Kebangsaan MalaysiaSelangorMalaysia

Personalised recommendations