Augmented Reality for Privacy-Sensitive Visual Monitoring

  • Piotr Szczuko
Part of the Communications in Computer and Information Science book series (CCIS, volume 429)


The paper presents a method for video anonymization and replacing real human silhouettes with virtual 3D figures rendered on the screen. Video stream is processed to detect and to track objects, whereas anonymization stage employs fast blurring method. Substitute 3D figures are animated accordingly to behavior of detected persons. Their location, movement speed, direction, and person height are taken into account during the animation and rendering phases. This approach requires a calibrated camera, and utilizes results of visual object tracking. In the paper a procedure for transforming objects visual features and bounding boxes into a script for animated figures is presented. This approach is validated subjectively, by assessing a correspondence between real image and the augmented one. Conclusions and future work perspectives are provided.


visual monitoring privacy augmented reality computer animation 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Anders, M.J.: Blender 2.49 Scripting. Packt Publishing (2010)Google Scholar
  2. 2.
    Bratt, B.: Rotoscoping. Focal Press (2012)Google Scholar
  3. 3.
  4. 4.
    Cederberg, J.N.: Projective Geometry. In: A Course in Modern Geometries. Undergraduate Texts in Mathematics, pp. 213–313. Springer (2001)Google Scholar
  5. 5.
    Cichowski, J., Czyzewski, A.: Reversible video stream anonymization for video surveillance systems based on pixels relocation and watermarking. In: 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops), pp. 1971–1977 (2011)Google Scholar
  6. 6.
    Czyżewski, A., Szwoch, G., Dalka, P., Szczuko, P., Ciarkowski, A., Ellwart, D., Merta, T., Łopatka, K., Kulasek, Ł., Wolski, J.: Multi-stage video analysis framework. In: Lin, W. (ed.) Video Surveillance, ch. 9, pp. 145–171. Intech (2011)Google Scholar
  7. 7.
    Dalka, P.: Detection and Segmentation of Moving Vehicles and Trains Using Gaussian Mixtures, Shadow Detection and Morphological Processing. Machine Graphics and Vision 15(3/4), 339–348 (2006)Google Scholar
  8. 8.
    Dalka, P., Szwoch, G., Szczuko, P., Czyżewski, A.: Video Content Analysis in the Urban Area Telemonitoring System. In: Tsihrintzis, G.A., et al. (eds.) Multimedia Services in Inteligent Environments, pp. 241–261. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  9. 9.
    Deutscher, J., Blake, A., Reid, I.D.: Articulated body motion capture by annealed particle filtering. In: Proc. IEEE Conf. on Computer Vision and Pattern Recognition, pp. 126–133 (2000)Google Scholar
  10. 10.
    ITU-T recommendation P.800: Methods for subjective determination of transmission quality (1996),
  11. 11.
    Kakadiaris, I., Metaxas, D.: Model-based estimation of 3D human motion. IEEE Tran. Pattern Analysis and Machine Intelligence 22(12), 1453–1459 (2000)CrossRefGoogle Scholar
  12. 12.
    Kehl, R., Van Gool, L.: Markerless tracking of complex human motions from multiple views. Computer Vision and Image Understanding 104(2-3), 190–209 (2006)CrossRefGoogle Scholar
  13. 13.
    Kotus, J., Dalka, P., Szczodrak, M., Szwoch, G., Szczuko, P., Czyżewski, A.: Multimodal Surveillance Based Personal Protection System. In: Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA), Poznan, pp. 100–105 (2013)Google Scholar
  14. 14.
    Krolewski, J., Gawrysiak, P.: The Mobile Personal Augmented Reality Navigation System. In: Czachórski, T., Kozielski, S., Stańczyk, U. (eds.) Man-Machine Interactions 2. AISC, vol. 103, pp. 105–113. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  15. 15.
    Laveau, S., Faugeras, O.: Oriented projective geometry for computer vision. In: Buxton, B.F., Cipolla, R. (eds.) ECCV 1996. LNCS, vol. 1064, pp. 147–156. Springer, Heidelberg (1996)CrossRefGoogle Scholar
  16. 16.
    Moshkovitz, M.: The Virtual Studio: Technology and Techniques. Focal Press (2000)Google Scholar
  17. 17.
    Mullen, T.: Mastering Blender, Sybex (2012)Google Scholar
  18. 18.
    PETS 2006 Bemchmark Data. In: IEEE Conference on Computer Vision and Pattern Recognition 2006 (2006),
  19. 19.
    Rumiński, D., Walczak, K.: Creation of Interactive AR Content on Mobile Devices. In: Abramowicz, W. (ed.) BIS 2013 Workshops. LNBIP, vol. 160, pp. 258–269. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  20. 20.
    Schreer, O., Kauff, P., Sikora, T. (eds.): 3D Videocommunication: Algorithms, concepts and real-time systems in human centred communication. Wiley (2005)Google Scholar
  21. 21.
    Szwoch, G., Dalka, P., Czyżewski, A.: Spatial Calibration of a Dual PTZ-Fixed Camera System for Tracking Moving Objects in Video. Journal of Imaging Science and Technology (JIST) 57(2), 1–10 (2013)CrossRefGoogle Scholar
  22. 22.
    Szczuko, P.: Hierarchical Estimation of Human Upper Body Based on 2D Observation Utilizing Evolutionary Programming and “Genetic Memory”. In: Dziech, A., Czyżewski, A. (eds.) MCSS 2011. CCIS, vol. 149, pp. 82–90. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  23. 23.
    Szczuko, P.: Genetic programming extension to APF-based monocular human body pose estimation. Journal of Multimedia Tools and Applications, Multimedia Tools and Applications 68, 177–192 (2014)CrossRefGoogle Scholar
  24. 24.
    Szwoch, G., Dalka, P., Ciarkowski, A., Szczuko, P., Czyzewski, A.: Visual Object Tracking System Employing Fixed and PTZ Cameras. Journal of Intelligent Decision Technologies 5(2), 177–188 (2011), Google Scholar
  25. 25.
    Szwoch, G., Dalka, P.: Layered background modeling for automatic detection of unattended objects in camera images. In: WIAMIS 2011: 12th International Workshop on Image Analysis for Multimedia Interactive Services, Delft (2011) (Preprint No. 50)Google Scholar
  26. 26.
    Tsai, R.Y.: A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf tv cameras and lenses. IEEE Journal of Robotics and Automation 3(4), 323–344 (1987)CrossRefGoogle Scholar
  27. 27.
    University of Maryland, Guide to Authoring Media Ground Truth with ViPER-GT,
  28. 28.
    Uustal, H., Baerga, E.: Gait Analysis. In: Cuccurullo, S. (ed.) Physical Medicine and Rehabilitation Board Review. Demos Medical Publishing, New York (2004),
  29. 29.
    Wikitude, augmented reality platform,

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Piotr Szczuko
    • 1
  1. 1.Multimedia Systems DepartmentGdańsk University of TechnologyGdanskPoland

Personalised recommendations