Abstract
We develop a simple and fast human tracking system based on skin-color using Kalman filter for humanoid robots. For our human tracking system we propose a fuzzy and probabilistic model of observation noise, which is important in Kalman filter implementation. The uncertainty of the observed candidate region is estimated by neural network. Neural network is also used for the verification of face-like regions obtained from skin-color information. Then the probability of observation noise is controlled based on the uncertainty value of the observation. Through the real-human tracking experiments we compare the performance of the proposed model with the conventional Gaussian noise model. The experimental results show that the proposed model enhances the tracking performance and also can compensate the biased estimations of the baseline system.
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References
Perez, P., Hue, C., Vermaak, J., Gangent, M.: Color-based Probabilistic Tracking. In: Heyden, A., Sparr, G., Nielsen, M., Johansen, P. (eds.) ECCV 2002. LNCS, vol. 2350, pp. 661–675. Springer, Heidelberg (2002)
Luo, R., Guo, Y.: Real-time Stereo Tracking of Multiple Moving Heads. In: IEEE ICCV Workshop, pp. 55–60 (2001)
Kawato, S., Ohya, J.: Automatic Skin-color Distribution Extraction for Face Detection and Tracking. In: ICDSP 2000, vol. 2II, pp. 1415–1418 (2000)
Grewal, M.S., Andrews, A.P.: Kalman Filtering: Theory and Practice Using Matlab. John Wiley & Sons, Chichester (2001)
Klein, L.A.: Sensor and Data Fusion: A Tool for Information Assessment and Decision Making. SPIE Press (2004)
Tomaz, F., Candeias, T., Shahbazkia, H.: Improved Automatic Skin Detection in Color Images. In: VIIth International Conference on Digital Image Computing, pp. 10–12 (2003)
Rowley, H.A., Baluja, S., Kanade, T.: Human Face Detection in Visual Scenes. CMU-CS-95-158, Carnegie Mellon University (1955)
Hsu, R.L.: Face Detection in Color Images. Department of Computer Science & Engineering, Michigan State University. MI 48824 (2004)
Vezhnevets, V., Andreeva, S.A.: A Survey on Pixel-Based Skin Color Detection Techniques. In: Proc. Graphicon 2003, pp. 85–92. Moscow State University (2003)
Ward, D.B., Lehmann, E.A., Williamson, R.R.: Particle Filtering Algorithms for Tracking an Acoustic Source in a Reverberant Environment. IEEE Trans. on Speech and Audio Processing 11, 826–836 (2003)
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© 2006 Springer-Verlag Berlin Heidelberg
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Kim, J.Y., Song, MG., Na, S.Y., Baek, SJ., Choi, S.H., Lee, J. (2006). Skin-Color Based Human Tracking Using a Probabilistic Noise Model Combined with Neural Network. In: Wang, J., Yi, Z., Zurada, J.M., Lu, BL., Yin, H. (eds) Advances in Neural Networks - ISNN 2006. ISNN 2006. Lecture Notes in Computer Science, vol 3972. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11760023_61
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DOI: https://doi.org/10.1007/11760023_61
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-34437-7
Online ISBN: 978-3-540-34438-4
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