Fast and Efficient Video Completion Using Object Prior Position

  • Sameh Zarif
  • Ibrahima Faye
  • Dayang Rohaya
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8237)


Reconstruction and repairing damaged parts after object removal of digital video is an important trend in artwork restoration. Video completion is an active subject in video processing, which deals with the recovery of the original data. Most previous video completion approaches consume more time in extensive search to find the best patch to restore the damaged frames. In addition to that, visual artifacts appear when the damaged area is large. In this paper, we present a fast and efficient video completion method without the extensive search process. The proposed method is based on the object prior positions and the temporal continuity of the video frames. The proposed method is fast and maintains the spatial and temporal consistency. In addition to that, it can handle the object size and posture change, non periodic motion, and non stationary background.


Video inpainting Video Completion Object Removal Texture Synthesis 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Tang, N.C., Chiou-ting, Chih-wen, Hong-yuan.: Video Inpainting on Digitized Vintage Films via Maintaining Spatiotemporal Continuity. IEEE Trans. on Multimedia 13(4), 602–614 (2011)Google Scholar
  2. 2.
    Hongying, Z., Yadong, W.: An Efficient Scratches Detection and Inpainting Algorithm for Old Film Restoration. In: IEEE Inter. Conf. on Information Technology and Computer Science, pp. 75–78 (2009)Google Scholar
  3. 3.
    Zarif, S., Faye, I., Rohaya, D.: Fast and Efficient Multichannel Image Completion Using Local Similarity. In: IEEE 21st Inter. Conf. on Pattern Recognition, pp. 3116–3119 (2012)Google Scholar
  4. 4.
    Sun, D., Yuan, L., Zhang, Y., Pan, G.: Structure-aware Image Completion with Texture Propagation. In: IEEE 6th Inter. Conf. on Image and Graphics (ICIG), pp. 199–204 (2011)Google Scholar
  5. 5.
    Lu, Z., Huang, H., Li, L., Cheng, D.: A Novel Exemplar-Based Image Completion Scheme With Adaptive TV-Constraint. In: IEEE 4th Inter. Conf. on Genetic and Evolutionary Computing, pp. 94–97 (2010)Google Scholar
  6. 6.
    Raimbault, F., Kokaram, A.: Stereo Video Inpainting. In: Proceeding of SPIE, vol. 7863, pp. 320–333 (2011)Google Scholar
  7. 7.
    Jia, Y., Hu, S., Martin, R.: Video Completion Using Tracking and Fragment Merging. Proceeding of Pacific Graphics 21(8-10), 601–610 (2005)Google Scholar
  8. 8.
    Bertalmio, M., Bertozzi, A.L., Sapiro, G.: Navier-stokes, fluid dynamics and image and video inpainting. In: IEEE CVPR, vol. I, pp. 355–363 (2001)Google Scholar
  9. 9.
    Bertalmio, M., Sapiro, G., Caselles, V., Ballester.: Image Inpainting. In: Proceeding of the ACM SIGGRAPH Conf. on Computer Graphics, pp. 417–424 (2000)Google Scholar
  10. 10.
    Jia, J., Wu, T., Tang, C.: Video repairing. In: Proceeding IEEE Computer Vision and Pattern Recognition (CVPR), pp. 364–371 (2004)Google Scholar
  11. 11.
    Zhang, Y., Xiao, J., Shah, M.: Motion Layer Based Object Removal in Video. In: 7 IEEE Workshop on Application of Computer Vision, pp. 516–521 (2005)Google Scholar
  12. 12.
    Wexler, Y., Shechtmam, E.: Irani Space Time Completion of Video. IEEE Trans. on Pattern Analysis and Machine Intelligence 29, 463–476 (2007)CrossRefGoogle Scholar
  13. 13.
    Patwardhan, K., Sapiro, G., Bertalmio, M.: Video Inpainting Under Constrained Camera Motion. IEEE Trans. on Image Processing 16(2), 545–553 (2007)MathSciNetCrossRefGoogle Scholar
  14. 14.
    Criminisi, A., Perez, P., Toyama, K.: Region Filling and Object Removal by Examplar-based Inpainting. IEEE Trans. Image Processing 13(9), 1200–1212 (2004)CrossRefGoogle Scholar
  15. 15.
    Shih, T.K., Tang, N.C., Hwang, J.N.: Exemplar Based Video Inpainting Without Ghost Shadow Artifacts by Maintaining Temporal Continuity. IEEE Trans. Circuit syst. Video Technol. 19(2), 347–360 (2009)CrossRefGoogle Scholar
  16. 16.
    Vijay, M., Samson, S., Zhao, J.: Efficient Object Based Video Inpainting. Proceeding of Pattern Recognition Letters 30(2), 168–179 (2009)CrossRefGoogle Scholar
  17. 17.
    Xia, A., Gui, Y., Yao, L., Ma, L., Lin, X.: Exemplar Based Object Removal in Video Using GMM. In: IEEE CMSP, pp. 366–370 (2011)Google Scholar
  18. 18.
    Mosleh, A., Bouguila, N., Hamza, A.: Video Completion Method Using Bandlet Transform. IEEE Trans. on Multimedia 14(6), 1591–1601 (2012)CrossRefGoogle Scholar
  19. 19.
    Criminisi, A., Cross, G., Blake, A., Kolmogorov, V.: Bilayer Segmentation of live Video. In: IEEE Inter. Conf. on Computer Vision and Pattern Recognition, pp. 53–60 (2006)Google Scholar
  20. 20.
    Drori, I., Cohen, D., Yeshurun, H.: Fragment-based Image Completion. Proceedings of SIGGRAPH 22, 303–312 (2003)CrossRefGoogle Scholar
  21. 21.
    Li, H., Wang, S., Zhang, W., Wu, M.: Image Inpainting Based on Scene Transform and Color Transform. Pattern Recognition Letters 31(7), 582–592 (2010)CrossRefGoogle Scholar
  22. 22.
    Zarif, S., Faye, I., Rohaya, D.: Static Object Removal from Video Scene Using Local Similarity. In: IEEE 9th Inter. Colloquium on Signal Processing and its Applications, pp. 54–57 (2013)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • Sameh Zarif
    • 1
  • Ibrahima Faye
    • 1
  • Dayang Rohaya
    • 1
  1. 1.Centre of Intelligent Signal and Imaging Research (CISIR)Universiti Teknologi PetronasMalaysia

Personalised recommendations