PSO-Particle Filter-Based Biometric Measurement for Human Tracking
Zhenyuan Xu and Junzo Watada
Graduate School of Information, Production and Systems, Waseda University, 2-7 Hibikino, Wakamatsu-ku, Kitakyushu, Fukuoka 808-0135, Japan
-  C. Sacchi and C. S. Regazzoni, “A distributed surveillance system for detection of abandoned objects in unmanned railway environments,” IEEE Trans. on Vehicular Technology, Vol.49, pp. 2013-2026, 2000.
-  M. Isard and A. Blake, “Contour tracking by stochastic propagation of conditional density,” Computer Vision-ECCV’96, Lecture Notes in Computer Science, Vol.1064, pp. 343-356, 1996.
-  D. W. Repperger, S. L. Ward, E. J. Hartzell, B. C. Glass, and W. C. Summers, “An Algorithm to Ascertain Critical Regions of Human Tracking Ability,” IEEE Trans. on Systems, Man and Cybernetics, Vol.9, pp. 183-196, 1979.
-  Z. B. Musa and J. Watada, “Video Tracking System: A survey,” An Int. J. of research and surveys (ICIC express letters), Vol.2, No.1, pp. 65-72, March 2008.
-  B. Ristic, S. Arulampalam, and N. Gordon, “Beyond the Kalman Filter: Particle Filters for Tracking Applications,” Artech House, 2004.
-  Z. H. Khan, I. Y. Gu, and A. G. Backhouse, “Robust Visual Object Tracking Using Multi-mode Anisotropic Mean Shift and Particle Filters,” IEEE Trans. on Circuits and Systems for Video Technology, Vol.21, pp. 74-87, 2011.
-  Y. Zhai, M. B. Yeary, S. Cheng, and N. Kehtarnavaz, “An Object-Tracing Algorithm Based on Multiple-Model Particle Filtering With State Partitioning,” IEEE Trans. on Instrumentation and Measurement, Vol.58, pp. 1797-1809, 2009.
-  J. MacCormick and A. Blake, “A probabilistic exclusion principle for tracking multiple objects,” Proc. Int. Conf. Comput. Vision, pp. 572-578, 1999.
-  J. Carpenter, P. Clifford, and P. Fearnhead, “Improved particle filter for nonlinear problems,” IEEE Proc. Radar, Sonar and Navigation, Vol.146, pp. 2-7, 1999.
-  L. Ye, Q. Zhang, and L. Guan, “Use hierarchical genetic particle filter to figure articulated human tracking,” IEEE Int. Conf. on Multimedia and Expo, pp. 1561-1564, 2008.
-  D. Crisan, P. Del Moral, and T. J. Lyons, “Discrete Filtering Using Branching and Interacting Particle Systems,” Markov Processes Related Fields, Vol.5, No.3, pp. 293-319, 1999.
-  S. J. McKenna and H. Nait-Charif, “Tracking human motion using auxiliary particle filters and iterated likelihood weighting,” Image and Vision Computing, Vol.25, Issue 6, pp. 852-862, 2007.
-  N. J. Gordon, D. J. Salmond, and A. F. M. Smith, “Novel approach to nonlinear/non-Gaussian Bayesian state estimation,” IEEE Proc. F, Vol.140, No.2, pp. 107-113, 1993.
-  G. Kitagawa, “Monte carlo filter and smoother for non-Gaussian nonlinear state space models,” J. of Computational and Graphical Statistics, Vol.5, No.1, pp. 1-25. 1996.
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