Foreground extraction using iterated graph cuts

Image analysis – Image segmentation

Reexamination Certificate

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

C382S225000

Reexamination Certificate

active

07660463

ABSTRACT:
Techniques are disclosed to provide more efficient and improved extraction of a portion of a scene without requiring excessive user interaction. More particularly, the extraction may be achieved by using iterated graph cuts. In an implementation, a method includes segmenting an image into a foreground portion and a background portion (e.g., where an object or desired portion to be extracted is present in the foreground portion). The method determines the properties corresponding to the foreground and background portions of the image. Distributions may be utilized to model the foreground and background properties. The properties may be color in one implementation and the distributions may be a Gaussian Mixture Model in another implementation. The foreground and background properties are updated based on the portions. And, the foreground and background portions are updated based on the updated foreground and background properties.

REFERENCES:
patent: 6009442 (1999-12-01), Chen et al.
patent: 6233575 (2001-05-01), Agrawal et al.
patent: 6592627 (2003-07-01), Agrawal et al.
patent: 2002/0048401 (2002-04-01), Boykov et al.
patent: 2002/0060650 (2002-05-01), Wakashiro et al.
patent: 2002/0122587 (2002-09-01), Lim et al.
patent: 2002/0135483 (2002-09-01), Merheim et al.
patent: 2002/0191861 (2002-12-01), Cheatle
patent: 2003/0043160 (2003-03-01), Elfving et al.
patent: 2003/0053658 (2003-03-01), Pavlidis
patent: 2003/0095707 (2003-05-01), Colmenarez et al.
patent: 2003/0123704 (2003-07-01), Farmer et al.
patent: 2005/0157926 (2005-07-01), Moravec et al.
patent: 2006/0242147 (2006-10-01), Gehrking et al.
Blake et. al, Interactive Image Segmentation Using an Adaptive GMMRF, 8th European Conference on Computer Vision, Prague, Czech Republic, May 11-14, 2004. Proceedings, Part I, May 10, 2004, Springer Berlin / Heidelberg, vol. 3021/2004, pp. 428-441.
Blake, A., et al., “Interactive Image Segmentation using an adaptive GMMRF model,” In Proc. European Conf. Computer Vision, 2004, pp. 1-14.
Boykov, Y., et al., “Interactive Graph Cuts for Optimal Boundary & Region Segmentation of Object in N-D Images,” In Proc. IEEE Int. Conf. on Computer Vision, Jul. 2001, vol. I, pp. 105-112.
Boykov, Y., et al., “Computing Geodesics and Minimal Surfaces via Graph Cuts,” In Proceedings of IEEE Int. Conf. on Computer Vision (ICVV), Nice, France, Jul. 2001, vol. I, pp. 26-33.
Caselles, V., et al., “Geodesic Active Contours,” In Proc. IEEE Int. Conf. on Computer Vision 22 (1), 1997, pp. 61-79.
Chuang, Y.-Y., et al., “A Bayesian Approach to Digital Matting,” In Proc. IEEE Conf. Computer Vision and Pattern Recog., 2001, 8 pages.
Kolmogorov, V., et al., “What Energy Functions can be Minimized via Graph Cuts?” In Proc. European Conf. Computer Vision, 2002, pp. 1-17.
Kwatra, V., et al., “Graphcut Textures: Image and Video Synthesis Using Graph Cuts,” Proce. ACM Siggraph, 2003, pp. 277-286.
Mortensen, E., et al., “Intelligent Scissors for Image Composition,” Proc. ACM Siggraph, 1995, pp. 191-198.
Mortensen, E., et al., “Toboggan-Based Intelligent Scissors with a Four Parameter Edge Model,” In Proc. IEEE Conf. Computer Vision and Pattern Recog., 1999, vol. 2, pp. 452-458.
Ruzon, M., et al., “Alpha Estimation in Natural Images,” In Proc. IEEE Conf. Comp. Vision and Pattern Recog., vol. 1, Jun. 2000, pp. 18-25.
Dempster, A. P., et al., “Maximum Likelihood from Incomplete Data via the $EM$ Algorithm,” Journal of the Royal Statistical Society, Series B, vol. 39, 1977, pp. 1-38.
Greig, D., et al., “Exact Maximum A Posteriori Estimation for Binary Images,” Journal of the Royal Statistical Society, Series B, vol. 51, No. 2, 1989, pp. 271-279.
Kass, M., et al., “Snakes: Active Contour Models,” Proc. IEEE Int. Conf. on Computer Vision, 1987, pp. 259-268.
“Adobe Photoshop User Guide”, pp. 55-57, Adobe Systems Inc., 1993.

LandOfFree

Say what you really think

Search LandOfFree.com for the USA inventors and patents. Rate them and share your experience with other people.

Rating

Foreground extraction using iterated graph cuts does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Foreground extraction using iterated graph cuts, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Foreground extraction using iterated graph cuts will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFUS-PAI-O-4193131

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.