|
|
Novel Active Contour Model for Object Tracking Based on the Potential Energy of Shape Restriction |
MIN Li1,2,3, HUANG ShaBai1, SHI ZeLin1, TANG YanDong1 |
1.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016 2.Graduate School, Chinese Academy of Sciences, Beijing 100039 3.College of Science, Shenyang Jianzhu University, Shenyang 110015 |
|
|
Abstract A novel active contour model for object tracking based on shape restriction is presented in this paper. Contour curvature prior is used to define potential energy of shape restriction and then integrated with region and gradient information of image to formulate the active contour model for tracking. With curvature restriction, this model can correct the wrong deformation caused by weak gradient of object boundary and cluttered background. It also maintains the overall structure of object and tracks object with irregular shape in image sequences. Furthermore, the initial contour is estimated using affine transformation based on the blockmatching. The model is applied to tracking IR car target in cluttered background and aircraft target in image sequences. Experimental results show that the proposed model has robust tracking performance in cluttered background and shapepreserving.
|
Received: 15 June 2004
|
|
|
|
|
[1] Kass M, Witkin A, Terzopoulos D. Snakes: Active Contour Models. International Journal of Computer Vision, 1987,1(4): 321-331 [2] Terzopoulos D, Szeliski R. Tracking with Kalman Snakes. In: Black A, Yuille A, eds. Active Vision. Cambridge, USA: MIT Press, 1993, 3-20 [3] Kim W, Lee J J. Visual Tracking Using Snake for Object’s Discrete Motion. In: Proc of the IEEE International Conference on Robotics and Automation. Seoul, Korea, 2001, 2608-2613 [4] Blake A, Isard M. Active Contour. London, UK: Springer-Verlag, 1998 [5] Zhong Y, Jain A K, Dubuisson-Jolly M P. Object Tracking Using Deformable Templates. IEEE Trans on Pattern Analysis and Machine Intelligence, 2000, 22(5): 544-549 [6] Bascle B, Bouthemy P, Deriche R, Meyer F G. Tracking Complex Primitives in an Image Sequence. In: Proc of the 12th International Conference on Pattern Recognition. Jerusalem, Israel, 1994, I: 426-431 [7] Curwen R, Blake A. Dynamic Contours: Real-Time Active Splines. In: Black A, Yuille A, eds. Active Vision. Cambridge, USA: MIT Press, 1992, 39-57 [8] Isard M, Blake A. Contour Tracking by Stochastic Propagation of Conditional Density. In: Proc of European Conference on Computer Vision. Cambridge, UK, 1996, 343-356 [9] Isard M, Blake A. Condensation-Conditional Density Propagation for Visual Tracking. International Journal of Computer Vision, 1998 , 29(1): 5-28 [10]Li P H, Zhang T W. A New B-Spline Active Contour Model. Chinese Journal of Computers, 2002, 25(12): 1348-1356 (in Chinese) (李培华,张田文.一种新的B样条主动轮廓线模型.计算机学报, 2002, 25(12): 1348-1356) [11] Wang Y X, Wang C S, Cheng Y M. Active Contours Guided by Optical Flow. Journal of Circuits and Systems, 2003, 8(1): 77-80 (in Chinese) (王以孝,王春声,程义民.引入光流法的活动轮廓模型.电路与系统学报, 2003, 8(1): 77-80) [12] Amini A, Tehrani S, Weymouth T E. Using Dynamic Programming for Minimizing the Energy of Active Contours in the Presence of Hard Constraints. In: Proc of the 2nd International Conference on Computer Vision. Tarpon Springs, USA, 1988, 95-99 [13] Jain A K, Zhong Y, et al. Deformable Template Models: A Review. Singal Processing, 1998, 71(2): 109-129 |
|
|
|