A Short-Term Biometric Based System for Accurate Personalized Tracking

  • Georgios StavropoulosEmail author
  • Nikolaos Dimitriou
  • Anastasios Drosou
  • Dimitrios Tzovaras
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11754)


Surveillance systems have long been in the focus of the research community. Although the accurate detection of the human presence in the scene is now possible even under extreme environmental conditions via the advanced modern camera sensors, efficient personalized tracking is still an open issue and a significant challenge for researchers addressing. Moreover, personalized tracking will not only enhance the tracking robustness but it can also find useful application in several commercial surveillance use-cases, ranging from security to occupancy statistics (i.e. per building, per space and per human). In this respect, this paper introduces a novel the biometric approach for enhanced privacy preserving human tracking based on a novel soft-biometric feature of humans. The moving blobs in the recorded scene can be easily detected in the colour images, while the human silhouettes are detected from the corresponding depth ones. The state-of-the-art 3D Weighted Walkthroughs (3DWW) transformation is applied on the extracted human 3D point cloud, forming thus, a short-term soft biometric signature. The re-authentication of the humans is performed via the comparison of their last valid signature with current one. A thorough analysis on the adjustment of the system’s optimal operational settings has been carried out and the experimental results illustrate the promising robustness, accuracy and efficiency on human tracking performance.


Motion detection Human tracking Surveillance Geometric identification 



This work is co-funded by the European Union (EU) within the SMILE project under grant agreement number 740931. The SMILE project is part of the EU Framework Program for Research and Innovation Horizon 2020.


  1. 1.
    Yun, Y., Song, C., Katsaggelos, A.K., Yanwei, L., Yi, Q.: Wireless video surveillance: a survey. IEEE Access 1, 646–660 (2013)CrossRefGoogle Scholar
  2. 2.
    Berretti, S., Bimbo, A.D., International Continence Society, Pala, P.: 3D Face recognition using isogeodesic stripes. IEEE Trans. Pattern Anal. Mach. Intell. 32(12), 2162–2177 (2010)CrossRefGoogle Scholar
  3. 3.
    Beymer, D.: Person counting using stereo. In: Workshop on Human Motion, pp. 127–133 (2000)Google Scholar
  4. 4.
    Black, J., Ellis, T., Rosin, P.: Multi-view image surveillance and tracking. In: IEEE Workshop on Motion and Video Computing (2002)Google Scholar
  5. 5.
    Comaniciu, D., Ramesh, V., Meer, P.: Kernel-based object tracking. IEEE Trans. Pattern Anal. Mach. Intell. 5, 564–575 (2003)CrossRefGoogle Scholar
  6. 6.
    Fleuret, F., Berclaz, J., Lengagne, R., Fua, P.: Multicamera people tracking with a probabilistic occupancy map. IEEE Trans. Pattern Anal. Mach. Intell. 30(2), 267–282 (2008)CrossRefGoogle Scholar
  7. 7.
    Focken, D., Stiefelhagen, R.: Towards vision-based 3D people tracking in a smart room. In: IEEE International Conference on Multimodal Interfaces (2002)Google Scholar
  8. 8.
    Drosou, A., Tzovaras, D., Moustakas, K., Petrou, M.: Systematic error analysis for the enhancement of biometric systems using soft biometrics. IEEE Sig. Process. Lett. 19(12), 833–836 (2012)CrossRefGoogle Scholar
  9. 9.
    Drosou, A., Ioannidis, D., Tzovaras, D., Moustakas, K., Petrou, M.: Activity related authentication using prehension biometrics. Pattern Recogn. 48(5), 1743–1759 (2015)CrossRefGoogle Scholar
  10. 10.
    Xu, X., Tang, J., Liu, X., Zhang, X.: Human behavior understanding for video surveillance: recent advance. In: 2010 IEEE International Conference in Systems Man and Cybernetics (SMC), pp. 3867–3873 (2010)Google Scholar
  11. 11.
    Jia, X., Lu, H., Yang, M.: Visual tracking via adaptive structural local sparse appearance model. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1822–1829 (2012)Google Scholar
  12. 12.
    Kang, J., Cohen, I., Medioni, G.: Tracking people in crowded scenes across multiple cameras. In: Proceedings of Asian Conference on Computer Vision (2004)Google Scholar
  13. 13.
    Mikic, I., Santini, S., Jain, R.: Video processing and integration from multiple cameras. In: Image Understanding Workshop (1998)Google Scholar
  14. 14.
    Mittal, A., Davis, L.: M2Tracker: a multi-view approach to segmenting and tracking people in a cluttered scene. Int. J. Comput. Vis. 51(3), 189–203 (2003) CrossRefGoogle Scholar
  15. 15.
    Otsuka, K., Mukawa, N.: Multi-view occlusion analysis for tracking densely populated objects based on 2D visual angles. In: Proceedings of the Conference on Computer Vision and Pattern Recognition (CVPR) (2004)Google Scholar
  16. 16.
    Salih, Y., Malik, A.: 3D tracking using particle filters. In: Proceedings of IEEE Instrumentation and Measurement Technology Conference (I2MTC), pp. 1–4 (2011)Google Scholar
  17. 17.
    Yang, D., Gonzales-Banos, H., Guibas, L.: Counting people in crowds with a real-time network of simple image sensors. In: International Conference on Computer Vision, pp. 122–129 (2003)Google Scholar
  18. 18.
    Krinidis, S., Stavropoulos, G., Ioannidis, D., Tzovaras, D.: A robust and real-time multi-space occupancy extraction system exploiting privacy-preserving sensors. In: International Symposium on Communications, Control and Signal Processing (2014)Google Scholar
  19. 19.
    De Silva, L.: Audiovisual sensing of human movements for home-care and security in a smart environment. Int. J. Smart Sens. Intell. Syst. 1, 220–245 (2008)Google Scholar
  20. 20.
    Scataglini, S., Andreoni, G., Gallant, J.: Smart clothing design issues in military applications. In: Ahram, T.Z. (ed.) AHFE 2018. AISC, vol. 795, pp. 158–168. Springer, Cham (2019). Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Georgios Stavropoulos
    • 1
    Email author
  • Nikolaos Dimitriou
    • 2
  • Anastasios Drosou
    • 2
  • Dimitrios Tzovaras
    • 2
  1. 1.Electrical and Computer Engineering DepartmentUniversity of PatrasPatrasGreece
  2. 2.Centre for Research and TechnologyInformation Technologies InstituteThessalonikiGreece

Personalised recommendations