Active contour method with separate global translation and local deformation

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5928 LNAI, Issue , 2009, Pages 876-884

  Zhu, Linlin ^a,b   Fan, Baojie ^a,b   Tang, Yandong ^a  

^a SHENYANG INSTITUTE OF AUTOMATION   (China)

^b UNIVERSITY OF CHINESE ACADEMY OF SCIENCES   (China)

Author keywords

Active contour; Global translation; Gradient flow; Local deformation

Indexed keywords

ACTIVE CONTOUR METHOD; ACTIVE CONTOURS; COMPUTATION COSTS; GRADIENT FLOW; LOCAL DEFORMATIONS; TRANSLATION MOTION;

COST REDUCTION; CURVE FITTING; DEFORMATION; ROBOTICS; TARGET TRACKING;

TRANSLATION (LANGUAGES);

EID: 76649100472     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-10817-4_86     Document Type: Conference Paper

References (18)

1. Kass, M., Witkin, A., Terzopoulos, D.: Snakes: Active contour models. International Journal of Computer Vision 1, 321-331 (1987)
2. Caselles, V., Catte, F., Coll, T., Dibos, F.: A geometric model for active contours in image processing. Numer. Math. 66, 1-31 (1993)
3. Osher, S., Sethian, J.A.: Fronts propagating with curvature dependent speed: algorithms based on Hamilton-Jacobi formulations. J. Comp. Phys. 79, 12-49 (1988)
4. Kichenassamy, S., Kumar, A., Olver, P.J., Tannenbaum, A., Yezzi, A.: Gradient flows and geometric active contour models. In: International Conference on Computer Vision, pp. 810-815 (1995)
5. Xu, C., Prince, J.L.: Snakes, Shapes, and Gradient Vector Flow. IEEE Transactions on Image Processing 7(3), 359-369 (1998)
6. Zhu, S.C., Lee, T.S., Yuille, A.L.: Region competition: Unifying snakes, region growing, energy/Bayes/MDL for multi-band image segmentation. International Conference on Computer Vision, 416-423 (1995)
7. Chan, T.F., Vese, L.A.: Active contours without edges. IEEE Trans. Image Processing 10(2), 266-277 (2001)
8. Yezzi, A., Tsai, A., Willsky, A.: A fully global approach to image segmentation via coupled curve evolution equations. Journal of Visual Communication and Image Representation 13, 195-216 (2002)
9. Kim, J., Fisher, J.W., Yezzi, A., Cetin, M., Willsky, A.S.: A nonparametric statistical method for image segmentation using information theory and curve evolution. IEEE Transactions on Image Processing 14, 1486-1502 (2005)
10. Leventon, M.E., Grimson, W.E.L., Faugeras, O.: Statistical shape influence in geodesic active contours. In: Proc. IEEE Comput. Soc. Conf. CVPR, vol. 1, pp. 316-323 (2000)
11. Chen, H.D., Tagare, S.T., Huang, F., Wilson, D., Gopinath, K.S., Briggs, R.W., Geiser, E.A.: Using prior shapes in geometric active contours in a variational framework. International Journal of Computer Vision 50(3), 315-328 (2002)
12. Cremers, D.: Dynamical statistical shape priors for level set based tracking. IEEE Transactions on Pattern Analysis and Machine Intelligence 28, 1262-1273 (2006)
13. Han, X., Xu, C., Prince, J.L.: A Topology Preserving Level Set Method for Geometric Deformable Models. IEEE Transactions on Pattern Analysis and Machine Intelligence 25(6), 755-768 (2003)
14. Sundaramoorthi, G., Yezzi, A.: More Than Topology Preserving Flows for Active Contours and Polygons. In: Tenth IEEE International Conference on Computer Vision, vol. 2, pp. 1276-1283 (2005)
15. Cremers, D., Rousson, M., Deriche, R.: A Review of Statistical Approaches to Level Set Segmentation: Integrating Color, Texture, Motion and Shape. International Journal of Computer Vision 72(2), 195-215 (2007)
16. Chan, T., Sandberg, B., Moelich, M.: Some Recent Developments in Variational Image Segmentation, University of California, Los Angeles: Los Angeles, CAM06-52, p. 36 (2006)
17. Charpiat, G., Maurel, P., Pons, J.P., Keriven, R., Faugeras, O.: Generalized Gradients: Priors on Minimization Flows. International Journal of Computer Vision 73(3), 325-344 (2007)
18. Sundaramoorthi, G., Yezzi, A.J., Mennucci, A.: Sobolev Active Contours. International Journal of Computer Vision 73(3), 109-120 (2007)