Abstract
Human contour provides important information in high level vision tasks such as activity recognition and human computer interaction where detailed analysis of shape deformation is required. In this paper, a real time region-based contour tracking algorithm is presented. The main advantage of our algorithm is the ability of tracking nonrigid objects such as human using an adaptive external speed function with fast level set method. The weighting parameter, λ i is adjusted to accommodate the situations in which the object being tracked and the background have similar intensity. Experimental results show the better performance of the proposed algorithm with adaptive weights.
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References
Yilmaz, A., Li, X., Shah, M.: Contour-based tracking with occlusion handling in video acquired using mobile cameras. IEEE Trans. on Pattern Analysis and Machine Intelligence 26(11) (November 2004)
Besson, S., Barlaund, M., Aubert, G.: Detection and trackign of moving objects using a new level set based method. In: Proc. International Conference on Pattern Recognition, September 2000, vol. 3, pp. 1100–1105 (2000)
Stauffer, C., Grimson, W.E.L.: Adaptive background mixture models for real-time tracking. In: IEEE Comptuer Society Conference on Computer Vision and Pattern Recognition, vol. 2 (1999)
Chan, T., Vese, L.: Active contours without edges. IEEE Trans. on Image Processing 10(2), 266–277 (2001)
Cremers, D.: Dynamical statistical shape priors for level set based tracking. IEEE Trans. on Pattern Analysis and Machine Intelligence (2006)
Kass, M., Witkin, A., Terzopolous, D.: Snakes: Active contour models. International Journal of Computer Vision 1, 321–331 (1987)
Mansouri, A.: Region tracking via level set pdes without motion computation. IEEE Trans. Pattern Analysis and Machine Intelligence 24, 947–961 (2002)
Paragios, N., Deriche, R.: Unifying boundary and region-based information for geodesic active tracking. In: IEEE Conference on Computer Vision and Pattern Recognition, Colorado, USA (1999)
Paragios, N., Deriche, R.: Geodesic active contours and level sets for the detection and tracking of moving objects. IEEE Trans. on Pattern Analysis and Machine Intelligence 22(3), 266–280 (2000)
Shi, Y., Clem Karl, W: Real-time tracking using level sets. Computer Vision and Pattern Recognition (June 2005)
Osher, S., Sethian, J.A.: Fronts propagating with curvature dependent speed: Algorithms based on hamiton-jacobi formulations. Journal of Computational Physics 79, 12–49 (1988)
Zhu, S., Yuille, A.: Region competition: Unifying snake/ballon, region growing, and bayes/mdl/energy for multi-band image segmentation. IEEE Trans. on Pattern Analysis and Machine Intelligence 18(9), 884–900 (1996)
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Thida, M., Chan, K.L., Eng, HL. (2006). An Improved Real-Time Contour Tracking Algorithm Using Fast Level Set Method. In: Chang, LW., Lie, WN. (eds) Advances in Image and Video Technology. PSIVT 2006. Lecture Notes in Computer Science, vol 4319. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11949534_70
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DOI: https://doi.org/10.1007/11949534_70
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-68297-4
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