Super pixel extraction via convexity induced boundary adaptation

Proceedings - IEEE International Conference on Multimedia and Expo

Volumn , Issue , 2013, Pages

  Tasli, H Emrah ^a,b   Cigla, Cevahir ^a   Gevers, Theo ^b   Alatan, A Aydin ^a  

^a MIDDLE EAST TECHNICAL UNIVERSITY   (Turkey)

^b UNIVERSITY OF AMSTERDAM   (Netherlands)

Author keywords

Convexity constraint; Image segmentation; Super pixel

Indexed keywords

BOUNDARY ADAPTATION; CONVEXITY CONSTRAINT; EXTRACTION ALGORITHMS; GEODESIC DISTANCES; REGION BOUNDARIES; SEGMENTATION ACCURACY; SUPER PIXELS;

EXHIBITIONS; EXTRACTION; IMAGE SEGMENTATION; ITERATIVE METHODS;

PIXELS;

EID: 84885657415     PISSN: 19457871     EISSN: 1945788X     Source Type: Conference Proceeding    
DOI: 10.1109/ICME.2013.6607465     Document Type: Conference Paper

References (18)

1. X. Ren and J. Malik, "Learning a classification model for segmentation," in Computer Vision, 2003. Proceedings. 9th IEEE International Conference on, Oct. 2003.
2. H. E. Tasli and A. A. Alatan, "Interactive object segmentation for mono and stereo applications: Geodesic prior induced graph cut energy minimization," ICCV Workshop Human Interaction on Compo Vision, 2011.
3. Soatto S. Ay vaci, A., "Motion segmentation with occlusions on the superpixel graph," Proc. of the Workshop on Dynamical Vision, Kyoto, Japan, 2009.
4. A. Lucchi, K. Smith, R. Achanta, V. Lepetit, and P. Fua, "A fully automated approach to segmentation of irregularly shaped cellular structures in em images," International Conference on Medical Image Computing (MICCAl) 2010.
5. A. Levinshtein, S. 1. Dickinson, and C. Sminchisescu, "Motion segmentation with occlusions on the superpixel graph," IEEE International Conference on Computer Vision, 2009.
6. Olga Veksler, Yuri Boykov, and Pari a Mehrani, "Superpixels and supervoxels in an energy optimization framework.," in Perspectives in neural computing, 2010.
7. Dorin Comaniciu, Peter Meer, and Senior Member, "Mean shift: A robust approach toward feature space analysis," IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002.
8. Jianbo Shi and I. Malik, "Normalized cuts and image segmentation," in IEEE Conference on Computer Vision and Pattern Recognition, 1997.
9. P. Felzenswalb and D. Huttenlocher, "Efficient graph based image segmentation," International Journal on Computer Vision, 2004.
10. Prince S. Warrell J. Mohammed U. Jones G Moore, A., "Efficient graph based image segmentation," International Conference on Computer Vision and Pattern Recognition, 2008.
11. L. Vincent and P. Soille, "Watersheds in digital spaces: an efficient algorithm based on immersion simulations," Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol. 13, no. 6, pp. 583-598, June 1991.
12. A. Levinshtein, A. Stere, K. N. Kutulakos, D. I. Fleet, S. J. Dickinson, and K. Siddiqi, "TurboPixels: Fast Superpixels Using Geometric Flows," IEEE Transactions on Pattern Analysis and Machine Intelligence, 2009.
13. G. Zeng, P. Wang, J. Wang, R. Gan, and H. Zha, "Structure-sensitive superpixels via geodesic distance," International Conference on Computer Vision, 2011.
14. G. Borgefors, "Distance transformations in digital images," Computer Vision, Graphics and Image Processing, vol. 34, no. 3, pp. 344371, 1986.
15. C. Cigla and A. A. Alatan, "Efficient graph-based image segmentation via speeded-up turbo pixels," in IEEE international Conference on Image Processing, 2010.
16. Dai Tang, Huazhu Fu, and Xiaochun Cao, "Topology preserved regular superpixel," 2012 IEEE International Conference on Multimedia and Expo.
17. Antonio Criminisi, Toby Sharp, and Andrew Blake, "Geos: Geodesic image segmentation," in European Conference on Computer Vision. 2008, Springer-Verlag.
18. E. W Dijkstra, "A note on two problems in connexion with graphs," Numerische Mathematik 1959.