Semi-supervised Learning for Anomalous Trajectory Detection
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[1] J Marques de Sa,et al. Incremental One-Class Learning with Bounded Computational Complexity , 2007 .
[2] Sameer Singh,et al. Novelty detection: a review - part 1: statistical approaches , 2003, Signal Process..
[3] Nicholas Ayache,et al. Smoothing and matching of 3-d space curves , 2005, International Journal of Computer Vision.
[4] Ian D. Reid,et al. A general method for human activity recognition in video , 2006, Comput. Vis. Image Underst..
[5] Sergio A. Velastin,et al. How close are we to solving the problem of automated visual surveillance? , 2008, Machine Vision and Applications.
[6] David C. Hogg,et al. Learning the Distribution of Object Trajectories for Event Recognition , 1995, BMVC.
[7] David C. Hogg,et al. Detecting inexplicable behaviour , 2004, BMVC.
[8] Nicholas Ayache,et al. Smoothing and matching of 3-d space curves , 1992, Other Conferences.
[9] Shaogang Gong,et al. Video Behavior Profiling for Anomaly Detection , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[10] Martial Hebert,et al. Semi-Supervised Self-Training of Object Detection Models , 2005, 2005 Seventh IEEE Workshops on Applications of Computer Vision (WACV/MOTION'05) - Volume 1.
[11] Jacob Goldberger,et al. Hierarchical Clustering of a Mixture Model , 2004, NIPS.
[12] S. Roberts. Novelty detection using extreme value statistics , 1999 .
[13] Tieniu Tan,et al. A system for learning statistical motion patterns , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[14] Helbing,et al. Social force model for pedestrian dynamics. , 1995, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.
[15] Robert P. W. Duin,et al. On the Choice of Smoothing Parameters for Parzen Estimators of Probability Density Functions , 1976, IEEE Transactions on Computers.