Abstract
Recently many methods for human articulated body tracking were proposed in the literature. These techniques are often computationally intensive and cannot be used for Human-Computer Interface. We propose in this article a real-time algorithm for upper body tracking with occultation handling. The tracking is based on an articulated body model, also used to automatically initialize the target. After an independent search of the most likely positions of each limb, a dynamic programming algorithm is used to find the best configuration according to the links between limbs. The self-occultations between the limbs are directly taken into account by the tracking algorithm and results show the interest of the proposed approach.
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References
Moeslund, T.B., Hilton, A., Krüger, V.: A survey of advances in vision-based human motion capture and analysis. Comput. Vis. Image Underst. 104(2), 90–126 (2006)
Haritaoglu, I., Harwood, D., Davis, L.S.: W4: Real-time surveillance of people and their actions. IEEE Trans. Pattern Anal. Mach. Intell. 22, 809–830 (2000)
Felzenszwalb, P.F., Huttenlocher, D.P.: Pictorial Structures for Object Recognition. Int. J. Comput. Vision 61(1), 55–79 (2005)
Ramanan, D., Forsyth, D.A., Zisserman, A.: Tracking People by Learning Their Appearance. IEEE Trans. Pattern Anal. Mach. Intell. 29(1), 65–81 (2007)
Ju, S.X., Black, M.J., Yacoob, Y.: Cardboard People: A Parameterized Model of Articulated Image Motion. In: Int. Conf. on Auto. Face and Gesture Recognition, pp. 38–44 (1996)
Demirdjian, D., Taycher, L., Shakhnarovich, G., Grauman, K., Darrell, T.: Avoiding the Streetlight Effect: Tracking by Exploring Likelihood Modes. In: IEEE Int. Conf. on Comput. Vis., vol. 1, pp. 357–364 (2005)
Sigal, L., Black, M.J.: Measure Locally, Reason Globally: Occlusion-sensitive Articulated Pose Estimation. IEEE Comput. Society Conf. on Comput. Vis. and Pattern Recognition 2, 2041–2048 (2006)
Fischler, M.A., Elschlager, R.A.: The representation and matching of pictorial structures. IEEE Transactions on Computer 22, 67–92 (1973)
Bernier, O., Cheung-Mon-Chan, P.: Real-Time 3D Articulated Pose Tracking using Particle Filtering and Belief Propagation on Factor Graphs. In: British Machine Vision Conf. (2006)
Felzenszwalb, P.F., Huttenlocher, D.P.: Efficient matching of pictorial structures. Comput. Vis. and Pattern Recognition 2, 66–73 (2000)
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© 2008 Springer-Verlag Berlin Heidelberg
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Para, E., Bernier, O., Achard, C. (2008). 2D Articulated Body Tracking with Self-occultations Handling. In: Perales, F.J., Fisher, R.B. (eds) Articulated Motion and Deformable Objects. AMDO 2008. Lecture Notes in Computer Science, vol 5098. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70517-8_16
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DOI: https://doi.org/10.1007/978-3-540-70517-8_16
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-70516-1
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