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Home > Archive>Volume 11, Issue 6, 2000 >751-757
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Review on Active Contour Model (Snake Model)
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    Abstract:

    In the field of traditional computer vision, the theory, in which the visual interpretation task comprises several levels that can be managed independently, has great influence on researchers. It presents that the information for accomplishing low level visual task can only be obtained from image itself. Kass et al. challenged the theory by developing an active contour model called Snake in 1987. Since then, this model has been enjoying a wide range of applications in the field of computer vision and significant advances have been made. The paper reviews the research, development and applications of the active contour model, and presents possible future research orientations.

    Reference
    1　 Kass M, Witkin A, Terzopoulous D. Snakes: active contour models. In: Brady I M, Rosenfield A eds. Proceedings of the 1st International Conference on Computer Vision. London: IEEE Computer Society Press, 1987. 259～268 2　 Cohen L D, Cohen I. A finite element method applied to new active contour models and 3D reconstruction from cross sections. In: Jsuji S, Kak A, Eklundh I O eds. Proceedings of the 3rd International Conference on Computer Vision. Osaka, Japan: IEEE Computer Society Press, 1990. 587～591 3　 Amini A A, Weymouth T E, Jain R C. Using dynamic programming for solving variational problem in vision. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1990,12(9):855～867 4　 Williams D J, Shab M. A fast algorithm for active contours and curvature estimation. CVGIP: Image Understanding,1992,55(1):14～26 5　 Lai K F, Chin R T. Deformable contours: modeling and extraction. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1995,17(11):1084～1090 6　 Cohen L D. On active contour models and balloons. CVGIP: Image Understanding, 1991,53(2):211～218 7　 Xu C, Prince J L. Snakes, shapes and gradient vector flow. IEEE Transactions on Image Processing, 1998,7(3):359～369 8　 Menet S, Saint-Mar P, Medion G B. Snakes: implementation and application to stereo. In: Fua P, Hansan A J eds. Proceedings of the DARPA Image Understanding Workshop. Pittsburgh, Pennsylanis: IEEE Computer Society Press, 1990. 720～726 9　 Storvik G. A Bayesian approach to dynamic contours through stochastic sampling and simulated Annealing. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1994,16(10):970～986 10　 Yuille A L, Mallinan P W, Cohen D S. Feature extraction from faces using deformable templates. International Journal on Computer Vision, 1992,8(2):133 ～144 11　 Staib L H, Duncan T S. Boundary finding with parametrically deformable models. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1992,14(11):1061～1075 12　 Lai K F, Chin R T. Deformable contours: modeling and extraction. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1995,17(11):1084～1090 13　 Jain A K, Zhong Y, Lakshmanan S. Object matching using deformable templates. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1996,18(3):267～278 14　 Jolly M P D, Lakshmanan S, Jain A K. Vechile segmentation and classification using deformable templates. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1996,18(3):293～308 15　 Zhou Yan-bo, Zhang Guang-zhi. Deformable objects contour extraction. Acta Electronic Sinia, 1998,26(7):133～137 (周彦博,张广志.可变形物体的轮廓的提取.电子学报,1998,26(7):133～137) 16　 Jia Chun-guang, Tan Ou, Duan Hui-long et al. Medical Image registration based on deformable contour. Journal of Computer Aided Design and Computer Graphics, 1999,11(2):115～119 (贾春光,谭鸥,段会龙等.基于变形轮廓的医学图像匹配方法.计算机辅助设计与图形学学报,1999,11(2):115～119) 17　 Terzpoulos D, Waters K. Analysis of facial images using physical and anatomical models. In: Jsujis, kak A, Ekeundh J O eds. Proceedings of the 3rd International Conference on Computer Vision. Washington: IEEE Computer Society Press, 1990. 727～732 18　 Szeliski R, Terzopoulos D. Physically-Based and probalistic modeling for computer vision. In: Vemuri B C ed. Proceedings SPIE 1570, Geometric Methods in Computer Vision. San Diego, CA: Society of Photo-Optical Instrumentation Engineers, 1991. 140～152 19　 Curwen R, Blake A. Dynamic contours: real-time active splines. In: Blake A, Yullie A eds. Active Vision. Cambridge, Massachusetts: MIT Press, 1992. 39～58 20　 Amini A A, Chen Y, Curwen R W et al. Coupled B-snake grids and constrained thin-plate splines for analysis of 2-D tissue deformations from tagged MRI. IEEE Transactions on Medical Imaging, 1998,17(3):344～356 21　 PeterFreund N. Robust tracking with spatio-velocity snakes: kalman filtering approach. In: Marendra A, Desai U eds. Proceedings of the 6th International Conference on Computer Vision. Bombay, India: IEEE Computer Society Press, 1998. 512～519 22　 Cipolla R, Blake A. Motion planning using image divergence and deformation. In: Blake A, Yullie A eds. Active Vision. Cambridge, Massachusetts: MIT Press, 1992. 189～202 23　 Cham T J, Cipolla R. Stereo coupled active contours. In: Grewe L ed. Proceedings of the International Conference on CVPR. San Juan, DuertoRico: IEEE Computer Society Press, 1997. 1094～1099
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李培华,张田文.主动轮廓线模型(蛇模型)综述.软件学报,2000,11(6):751-757

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History
  • Received:October 10,1999
  • Revised:January 21,2000
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