Abstract
This paper presents a novel binary speed term for tracking objects with the help of active contours. The speed, which can be 0 or 1, is determined by local nonlinear filters, and not by the strength of the gradient as is common for active contours. The speed has been designed to match the nature of a recent fast level-set evolution algorithm. The resulting active contour method is used to track objects for which probability distributions of pixel intensities for the background and for the object cannot be reliably estimated.
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References
Isard, M., Blake, A.: Icondensation: Unifying low-level and high-level tracking in a stochastic framework. In: Burkhardt, H., Neumann, B. (eds.) ECCV 1998. LNCS, vol. 1407, pp. 893–908. Springer, Heidelberg (1998)
Kass, M., Witkin, A., Terzopoulos, D.: Snakes: Active contour models. International Journal of Computer Vision 1(4), 321–331 (1988)
Cootes, T.F., Taylor, C.J., Cooper, D.H., Graham, J.: Active shape models – their training and application. Comput. Vis. Image Underst. 61(1), 38–59 (1995)
Caselles, V., Kimmel, R., Sapiro, G.: Geodesic active contours. Int. J. Comput. Vision 22(1), 61–79 (1997)
Paragios, N., Deriche, R.: Geodesic active contours for supervised texture segmentation. In: CVPR 1999. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 2, p. 2422. IEEE Computer Society, Los Alamitos (1999)
Osher, S., Sethian, J.A.: Fronts propagating with curvature-dependent speed: Algorithms based on Hamilton-Jacobi formulations. Journal of Computational Physics 79, 12–49 (1988)
Paragios, N., Deriche, R.: Geodesic active contours and level sets for the detection and tracking of moving objects. IEEE Transactions on Pattern Analysis and Machine Intelligence 22(3), 266–280 (2000)
Ecabert, T.O.: Variational image segmentation by unifying region and boundary information. In: 16th International Conference on Pattern Recognition (2002)
Chan, T., Vese, L.: Active contours without edges. IEEE Trans. Image Processing 10, 266–277 (2001)
Mansouri, A.R.: Region tracking via level set pdes without motion computation. IEEE Trans. Pattern Anal. Machine Intell. 24(7), 947–961 (2002)
Yilmaz, A., Li, X., Shah, M.: Contour-based object tracking with occlusion handling in video acquired using mobile cameras. IEEE Trans. Pattern Anal. Machine Intell. 26(11), 1531–1536 (2004)
Roy, T., Debreuve, É., Barlaud, M., Aubert, G.: Segmentation of a vector field: dominant parameter and shape optimization. Journal of Mathematical Imaging and Vision 24(2), 259–276 (2006)
Freedman, D., Zhang, T.: Active contours for tracking distributions. IEEE Transactions on Image Processing 13(4), 518–526 (2004)
Comaniciu, D., Ramesh, V., Meer, P.: Real-time tracking of non-rigid objects using mean shift. In: IEEE Conf. Computer Vision and Pattern Recognition, IEEE Computer Society Press, Los Alamitos (2000)
Shi, Y., Karl, W.C.: Real-time tracking using level sets. In: CVPR 2005. Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Washington, DC, USA, pp. 34–41. IEEE Computer Society Press, Los Alamitos (2005)
Sethian, J.: Level Set Methods and Fast Marching Methods. Evolving Interfaces in Computational Geometry, Fluid Mechanics, Computer Vision, and Materials Science. Cambridge University Press, Cambridge (1999)
Shi, Y., Karl, W.: A fast level set method without solving pdes. In: IEEE International Conference on Acoustics, Speech, and Signal Processing, IEEE Computer Society Press, Los Alamitos (2005)
Smith, S.M., Brady, J.M.: Susan–a new approach to low level image processing. Int. J. Comput. Vision 23(1), 45–78 (1997)
Comaniciu, D., Meer, P.: Mean shift: A robust approach toward feature space analysis. IEEE Trans. Pattern Analysis Machine Intell. 24, 603–619 (2002)
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Darolti, C., Mertins, A., Hofmann, U.G. (2007). A Fast Level-Set Method for Accurate Tracking of Articulated Objects with an Edge-Based Binary Speed Term. In: Blanc-Talon, J., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2007. Lecture Notes in Computer Science, vol 4678. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74607-2_75
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DOI: https://doi.org/10.1007/978-3-540-74607-2_75
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