Abstract
This paper presents active contours based method for hand tracking using color information. The main problem in active contours based approach is that results are very sensitive to location of the initial curve. Initial curve far form the object induces more heavy computational cost, low accuracy of results, as well as missing the object that has a large movement. Therefore, this paper presents a hand tracking method using a mean shift algorithm and active contours. The proposed method consists of two steps: hand localization and hand extraction. In the first step, the hand location is estimated using mean shift. And the second step, at the location, evolves the initial curve using an active contour model. To assess the effectiveness of the proposed method, it is applied to real image sequences which include moving hand.
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References
Shan, C., Wei, Y., Tan, T., Ojardias, F.: Real Time Hand Tracking by Combining Particle Filtering and Mean Shift. In: Proceeding of the Sixth IEEE International Conference on Automatic Face and Gesture Recognition, pp. 669–674 (2004)
Freedman, D., Zhang, T.: Active Contours for Tracking Distributions. IEEE Transactions on Image Processing 13(4), 518–526 (2004)
Chan, T.F., Vese, L.A.: Active Contours Without Edges. IEEE Transactions on Image Processing 10(2), 266–277 (2001)
Gastaud, M., Barlaud, M., Aubert, G.: Combining Shape Prior and Statistical Features for Active Contour Segmentation. IEEE Transactions on Circuits and Systems for Video Technology 14(5), 726–734 (2004)
Kim, K.I., Jung, K., Kim, J.H.: Texture-Based Approach for Text Detection in Image Using Support Vector Machines and Continuously Adaptive Mean Shift Algorithm. IEEE Transactions on Pattern Analysis and Machine Intelligence 25(12), 1631–1639 (2003)
Bradski, G.R.: Computer Vision Face Tracking For Use in a Perceptual User Interface. Intel Technology Journal 2nd quarter, 1–15 (1998)
Jaffre, G., Crouzil, A.: Non-rigid Object Localization From Color Model Using Mean Shift. In: Proceedings of the International Conference on Image Processing, vol. 3, pp. 317–319 (2003)
Zhu, S.C., Yuille, A.: Region Competition: Unifying Snakes, Region Growing, and Bayes/MDL for Multiband Image Segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence 18(9), 884–900 (1996)
Mansouri, A.: Region Tracking via Level Set PDEs without Motion Computation. IEEE Transactions on Pattern Analysis and Machine Intelligence 24(7), 947–961 (2002)
Borgefors, G.: Hierarchical Chamfer Matching: A Parametric Edge Matching Algorithm. IEEE Transactions on Pattern Analysis and Machine Intelligence 10(11), 849–865 (1998)
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© 2005 Springer-Verlag Berlin Heidelberg
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Chang, J.S., Kim, E.Y., Jung, K., Kim, H.J. (2005). Real Time Hand Tracking Based on Active Contour Model. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2005. ICCSA 2005. Lecture Notes in Computer Science, vol 3483. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11424925_104
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DOI: https://doi.org/10.1007/11424925_104
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25863-6
Online ISBN: 978-3-540-32309-9
eBook Packages: Computer ScienceComputer Science (R0)