Studentized Dynamical System for Robust Object Tracking
暂无分享,去创建一个
[1] BlakeAndrew,et al. C ONDENSATION Conditional Density Propagation forVisual Tracking , 1998 .
[2] B. Ripley,et al. Robust Statistics , 2018, Wiley Series in Probability and Statistics.
[3] Chuanhai Liu. ML Estimation of the MultivariatetDistribution and the EM Algorithm , 1997 .
[4] Steve R. Waterhouse,et al. Bayesian Methods for Mixtures of Experts , 1995, NIPS.
[5] Thomas S. Huang,et al. JPDAF based HMM for real-time contour tracking , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.
[6] Christopher M. Bishop,et al. Robust Bayesian Mixture Modelling , 2005, ESANN.
[7] D. Ruppert. Robust Statistics: The Approach Based on Influence Functions , 1987 .
[8] Heng Tao Shen,et al. Principal Component Analysis , 2009, Encyclopedia of Biometrics.
[9] A. Zellner. Bayesian and Non-Bayesian Analysis of the Regression Model with Multivariate Student- t Error Terms , 1976 .
[10] David Mackay,et al. Probable networks and plausible predictions - a review of practical Bayesian methods for supervised neural networks , 1995 .
[11] Michel Verleysen,et al. Robust Bayesian clustering , 2007, Neural Networks.
[12] Charles M. Bishop. Variational principal components , 1999 .
[13] Andrew Blake,et al. Probabilistic Tracking with Exemplars in a Metric Space , 2002, International Journal of Computer Vision.
[14] Neil D. Lawrence,et al. Variational inference for Student-t models: Robust Bayesian interpolation and generalised component analysis , 2005, Neurocomputing.
[15] Michael J. Black,et al. EigenTracking: Robust Matching and Tracking of Articulated Objects Using a View-Based Representation , 1996, International Journal of Computer Vision.
[16] Yong Li,et al. Robust Bayesian PCA with Student’s t-distribution: The variational inference approach , 2008, 2008 15th IEEE International Conference on Image Processing.
[17] Ming-Hsuan Yang,et al. Incremental Learning for Visual Tracking , 2004, NIPS.
[18] Frank Dellaert,et al. A Rao-Blackwellized particle filter for EigenTracking , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..
[19] Chuanhai Liu,et al. ML Estimation of the Multivariate t Distribution and the EM Algorithm , 1997 .
[20] David J. Fleet,et al. Robust online appearance models for visual tracking , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.
[21] Keinosuke Fukunaga,et al. Introduction to statistical pattern recognition (2nd ed.) , 1990 .
[22] David J. Fleet,et al. Robust Online Appearance Models for Visual Tracking , 2003, IEEE Trans. Pattern Anal. Mach. Intell..
[23] Yong Li,et al. Coupled Hidden Markov Models for Robust EO/IR Target Tracking , 2007, 2007 IEEE International Conference on Image Processing.
[24] Pavel Pudil,et al. Introduction to Statistical Pattern Recognition , 2006 .
[25] Michael E. Tipping,et al. A Variational Approach to Robust Regression , 2001, ICANN.
[26] Michael E. Tipping,et al. Probabilistic Principal Component Analysis , 1999 .
[27] Sam T. Roweis,et al. EM Algorithms for PCA and SPCA , 1997, NIPS.
[28] David J. C. MacKay,et al. Comparison of Approximate Methods for Handling Hyperparameters , 1999, Neural Computation.
[29] Frank Dellaert,et al. Robust Generative Subspace Modeling: The Subspace t Distribution , 2004 .
[30] J. Hardin,et al. Generalized Linear Models and Extensions , 2001 .
[31] Guangyu Wang,et al. Breakdown points of t-type regression estimators , 2000 .
[32] Ming-Hsuan Yang,et al. Incremental Learning for Robust Visual Tracking , 2008, International Journal of Computer Vision.
[33] Yong Li,et al. An EM algorithm for robust Bayesian PCA with student’s t-distribution , 2008, 2008 15th IEEE International Conference on Image Processing.
[34] Michel Verleysen,et al. Robust probabilistic projections , 2006, ICML.
[35] Frank Dellaert,et al. MCMC-based particle filtering for tracking a variable number of interacting targets , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[36] Michael Isard,et al. CONDENSATION—Conditional Density Propagation for Visual Tracking , 1998, International Journal of Computer Vision.