International Conference on Image Analysis and Processing

ICIAP 2015: Image Analysis and Processing — ICIAP 2015 pp 56-65 | Cite as

Real-Time Foreground Segmentation with Kinect Sensor

  • Luigi Cinque
  • Alessandro Danani
  • Piercarlo Dondi
  • Luca Lombardi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9280)

Abstract

In the last years, economic multichannel sensors became very widespread. The most known of these devices is certainly the Microsoft Kinect, able to provide at the same time a color image and a depth map of the scene. However Kinect focuses specifically on human-computer interaction, so the SDK supplied with the sensors allows to achieve an efficient detection of foreground people but not of generic objects. This paper presents an alternative and more general solution for the foreground segmentation and a comparison with the standard background subtraction algorithm of Kinect. The proposed algorithm is a porting of a previous one that works on a Time-of-Flight camera, based on a combination of a Otsu thresholding and a region growing. The new implementation exploits the particular characteristic of Kinect sensor to achieve a fast and precise result.

Keywords

Segmentation Background subtraction Kinect Depth imagery 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Dondi, P., Lombardi, L.: Fast real-time segmentation and tracking of multiple subjects by time-of-flight camera. In: Proceedings of 6th International Conference on Computer Vision Theory and Applications (VISAPP 2011), pp. 582–587 (2011)Google Scholar
  2. 2.
    Dondi, P., Lombardi, L., LaRosa, A., Cinque, L.: Automatic image matting fusing time-of-flight and color cameras data streams. In: Proceedings of 8th International Conference on Computer Vision Theory and Applications (VISAPP 2013), vol. 1, pp. 231–237 (2013)Google Scholar
  3. 3.
    Wang, J., Agrawala, M., Cohen, M.F.: Soft scissors: an interactive tool for realtime high quality matting. In: ACM SIGGRAPH 2007 Papers (SIGGRAPH 2007), Article 9, pp 1–6. ACM (2007)Google Scholar
  4. 4.
    Zhang, Z.: Microsoft Kinect Sensor and Its Effect. IEEE MultiMedia 19(2), 4–10 (2012)CrossRefGoogle Scholar
  5. 5.
    Smisek, J., Jancosek, M., Pajdla, T.: 3D with kinect. In: 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops), pp. 1154–1160 (2011)Google Scholar
  6. 6.
    Wang, J., Cohen, M.F.: Image and video matting: a survey. Found. Trends. Comput. Graph. Vis. 3(2), 97–175 (2007)CrossRefGoogle Scholar
  7. 7.
    Lu, T., Li, S.: Image matting with color and depth information. In: 2012 21st International Conference on Pattern Recognition (ICPR), pp. 3787–3790 (2012)Google Scholar
  8. 8.
    Cho, J.-H., Lee, K.H., Aizawa, K.: Enhancement of Depth Maps With Alpha Channel Estimation for 3-D Video. IEEE Journal of Selected Topics in Signal Processing 6(5), 483–494 (2012)Google Scholar
  9. 9.
    Braham, M., Lejeune, A., Van Droogenbroeck, M.: A physically motivated pixel-based model for background subtraction in 3D images. In: 2014 International Conference on 3D Imaging (IC3D), pp. 1–8 (2014)Google Scholar
  10. 10.
    Abramov, A., Pauwels, K., Papon, J., Worgotter, F., Dellen, B.: Depth-supported real-time video segmentation with the kinect. In: 2012 IEEE Workshop on Applications of Computer Vision (WACV), pp. 457–464 (2012)Google Scholar
  11. 11.
    Kolb, A., Barth, E., Koch, R., Larsen, R.: Time-of-Flight cameras in computer graphics. Journal of Computer Graphics Forum 29, 141–159 (2010)Google Scholar
  12. 12.
    Bianchi, L., Gatti, R., Lombardi, L., Lombardi, P.: Tracking without background model for time-of-flight cameras. In: Wada, T., Huang, F., Lin, S. (eds.) PSIVT 2009. LNCS, vol. 5414, pp. 726–737. Springer, Heidelberg (2009) CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Luigi Cinque
    • 1
  • Alessandro Danani
    • 2
  • Piercarlo Dondi
    • 2
  • Luca Lombardi
    • 2
  1. 1.Department of Computer ScienceSapienza University of RomeRomaItaly
  2. 2.Department of Electrical, Computer and Biomedical EngineeringUniversity of PaviaPaviaItaly

Personalised recommendations