CFP last date
20 May 2024
Reseach Article

Exemplar-based Video Inpainting for Occluded Objects

by Vaishali U. Gaikwad, P. V. Kulkarni
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 81 - Number 13
Year of Publication: 2013
Authors: Vaishali U. Gaikwad, P. V. Kulkarni
10.5120/14075-2419

Vaishali U. Gaikwad, P. V. Kulkarni . Exemplar-based Video Inpainting for Occluded Objects. International Journal of Computer Applications. 81, 13 ( November 2013), 29-31. DOI=10.5120/14075-2419

@article{ 10.5120/14075-2419,
author = { Vaishali U. Gaikwad, P. V. Kulkarni },
title = { Exemplar-based Video Inpainting for Occluded Objects },
journal = { International Journal of Computer Applications },
issue_date = { November 2013 },
volume = { 81 },
number = { 13 },
month = { November },
year = { 2013 },
issn = { 0975-8887 },
pages = { 29-31 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume81/number13/14075-2419/ },
doi = { 10.5120/14075-2419 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:56:00.544196+05:30
%A Vaishali U. Gaikwad
%A P. V. Kulkarni
%T Exemplar-based Video Inpainting for Occluded Objects
%J International Journal of Computer Applications
%@ 0975-8887
%V 81
%N 13
%P 29-31
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The process of repairing damaged area or reconstructing specific area or removing unwanted objects from video is known as video inpainting. Most of the automatic techniques are available to deal with this problem but most of them are unable to repair large holes. To get sharp inpainted area, in this paper we have proposed an efficient algorithm using exemplar-based technique. Here, considered static camera which gives video having stationery background with moving foreground. To detect the region of moving objects we apply edge detection technique. Once object region detected priority assignment to the patches is applied. A natural image has structures and textures. Structure sparsity was measure to find similarities of the patches. The patch having higher sparseness is then selected and its priority is set which is the highest priority among the patches. This patch is then used for further inpainting.

References
  1. Criminisi, P. Perez, and K. Toyama, "Region filling and object removal by examplar-based image inpainting," IEEE Trans. Image Process. ,vol. 13, pp. 1200–1212, 2004.
  2. M. Bertalmio, G. Sapiro, V. Caselles, and C. Ballester, "Image inpainting," in Proc. SIGGRAPH, 2000, pp. 417–424.
  3. M. Bertalmio, A. L. Bertozzi, and G. Sapiro, "Navier–Strokes, fluid dynamics, and image and video inpainting," in Proc. IEEE Computer Society Conf. Computer Vision and Pattern Recognition, pp. 417–424, 2001.
  4. Y. Wexler, E. Shechtman, and M. Irani, "Space-time video completion," Proceedings. 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 1, 2004
  5. K. A. Patwardhan, G. Sapiro, and M. Bertalmio. "Video inpainting of occluding and occluded objects", in Proc. ICIP 2005. , Vol. II, pp. 69-72.
  6. Soon-Yong-Park, Chang-Joon-Park, and Inho Lee, "Moving Object Removal and Background Completion in a Video Sequence"
  7. J. Jia, T. Wu, Y. Tai, and C. Tang. "Video repairing: Inference of foreground and background under severe occlusion", Proceedings. 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Vol. I, pp. 364-371, 2004.
  8. Y. Zhang, J. Xiao, and M. Shah, "Motion layer based object removal in videos," 2005 Workshop on Applications of Computer Vision, 2005.
Index Terms

Computer Science
Information Sciences

Keywords

Inpainting texture synthesis patch.