Learning spatial context from tracking using penalised likelihoods
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[1] Hayit Greenspan,et al. A Probabilistic Framework for Spatio-Temporal Video Representation & Indexing , 2002, ECCV.
[2] William D. Penny,et al. Bayesian Approaches to Gaussian Mixture Modeling , 1998, IEEE Trans. Pattern Anal. Mach. Intell..
[3] J. Rissanen,et al. Modeling By Shortest Data Description* , 1978, Autom..
[4] David L. Dowe,et al. MML clustering of multi-state, Poisson, von Mises circular and Gaussian distributions , 2000, Stat. Comput..
[5] Volker Tresp,et al. Averaging, maximum penalized likelihood and Bayesian estimation for improving Gaussian mixture probability density estimates , 1998, IEEE Trans. Neural Networks.
[6] Chin-Hui Lee,et al. Maximum a posteriori estimation for multivariate Gaussian mixture observations of Markov chains , 1994, IEEE Trans. Speech Audio Process..
[7] Bin Yu,et al. Model Selection and the Principle of Minimum Description Length , 2001 .
[8] David C. Hogg,et al. Learning the distribution of object trajectories for event recognition , 1996, Image Vis. Comput..
[9] D. Rubin,et al. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .
[10] Shaogang Gong,et al. Data Driven Gesture Model Acquisition using Minimum Description Length , 2001 .
[11] José M. N. Leitão,et al. On Fitting Mixture Models , 1999, EMMCVPR.
[12] W. Eric L. Grimson,et al. Learning Patterns of Activity Using Real-Time Tracking , 2000, IEEE Trans. Pattern Anal. Mach. Intell..
[13] King-Sun Fu,et al. IEEE Transactions on Pattern Analysis and Machine Intelligence Publication Information , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[14] Tim J. Ellis,et al. Automatic learning of an activity-based semantic scene model , 2003, Proceedings of the IEEE Conference on Advanced Video and Signal Based Surveillance, 2003..