Video anomaly detection using deep incremental slow feature analysis network
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Xing Hu | Shiqiang Hu | Yingping Huang | Huanlong Zhang | Hanbing Wu | Shiqiang Hu | Huanlong Zhang | Yingping Huang | Xing Hu | Hanbing Wu
[1] Yunqian Ma,et al. Event detection using local binary pattern based dynamic textures , 2009, 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.
[2] Shaogang Gong,et al. Video Behavior Profiling for Anomaly Detection , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[3] Jürgen Schmidhuber,et al. Incremental Slow Feature Analysis: Adaptive Low-Complexity Slow Feature Updating from High-Dimensional Input Streams , 2012, Neural Computation.
[4] David C. Hogg,et al. Detecting inexplicable behaviour , 2004, BMVC.
[5] Shaogang Gong,et al. Learning Behavioural Context , 2012, International Journal of Computer Vision.
[6] Niko Wilbert,et al. Slow feature analysis , 2011, Scholarpedia.
[7] Junsong Yuan,et al. Abnormal event detection in crowded scenes using sparse representation , 2013, Pattern Recognit..
[8] Hua Yang,et al. The Large-Scale Crowd Behavior Perception Based on Spatio-Temporal Viscous Fluid Field , 2013, IEEE Transactions on Information Forensics and Security.
[9] Yinghuan Shi,et al. Real-Time Abnormal Event Detection in Complicated Scenes , 2010, 2010 20th International Conference on Pattern Recognition.
[10] Jean-Marc Odobez,et al. Topic models for scene analysis and abnormality detection , 2009, 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops.
[11] Björn Ommer,et al. Video parsing for abnormality detection , 2011, 2011 International Conference on Computer Vision.
[12] Junsong Yuan,et al. Sparse reconstruction cost for abnormal event detection , 2011, CVPR 2011.
[13] Pascal Vincent,et al. Representation Learning: A Review and New Perspectives , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[14] Changsheng Li,et al. Sparse representation for robust abnormality detection in crowded scenes , 2014, Pattern Recognit..
[15] Matthieu Cord,et al. Dynamic Scene Classification: Learning Motion Descriptors with Slow Features Analysis , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.
[16] Yandong Tang,et al. Video Anomaly Search in Crowded Scenes via Spatio-Temporal Motion Context , 2013, IEEE Transactions on Information Forensics and Security.
[17] Chabane Djeraba,et al. Real-time crowd motion analysis , 2008, 2008 19th International Conference on Pattern Recognition.
[18] Chabane Djeraba,et al. An entropy approach for abnormal activities detection in video streams , 2012, Pattern Recognit..
[19] Laurenz Wiskott,et al. Slow feature analysis yields a rich repertoire of complex cell properties. , 2005, Journal of vision.
[20] Kristen Grauman,et al. Observe locally, infer globally: A space-time MRF for detecting abnormal activities with incremental updates , 2009, CVPR.
[21] Aggelos K. Katsaggelos,et al. A Dynamic Hierarchical Clustering Method for Trajectory-Based Unusual Video Event Detection , 2009, IEEE Transactions on Image Processing.
[22] Alberto Del Bimbo,et al. Multi-scale and real-time non-parametric approach for anomaly detection and localization , 2012, Comput. Vis. Image Underst..
[23] Qi Wang,et al. Online Anomaly Detection in Crowd Scenes via Structure Analysis , 2015, IEEE Transactions on Cybernetics.
[24] Hichem Snoussi,et al. Detection of Abnormal Visual Events via Global Optical Flow Orientation Histogram , 2014, IEEE Transactions on Information Forensics and Security.
[25] Ramin Mehran,et al. Abnormal crowd behavior detection using social force model , 2009, CVPR.
[26] Terrence J. Sejnowski,et al. Slow Feature Analysis: Unsupervised Learning of Invariances , 2002, Neural Computation.
[27] Bonny Banerjee,et al. Online Detection of Abnormal Events Using Incremental Coding Length , 2015, AAAI.
[28] Qingshan Liu,et al. Abnormal detection using interaction energy potentials , 2011, CVPR 2011.
[29] Qi Zhu,et al. Abnormal crowd behavior detection by using the particle entropy , 2014 .
[30] Nuno Vasconcelos,et al. Anomaly detection in crowded scenes , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[31] Gian Luca Foresti,et al. Trajectory-Based Anomalous Event Detection , 2008, IEEE Transactions on Circuits and Systems for Video Technology.
[32] Niko Wilbert,et al. Invariant Object Recognition and Pose Estimation with Slow Feature Analysis , 2011, Neural Computation.
[33] VARUN CHANDOLA,et al. Anomaly detection: A survey , 2009, CSUR.
[34] Brian C. Lovell,et al. Improved anomaly detection in crowded scenes via cell-based analysis of foreground speed, size and texture , 2011, CVPR 2011 WORKSHOPS.
[35] Sridha Sridharan,et al. Unusual Scene Detection Using Distributed Behaviour Model and Sparse Representation , 2012, 2012 IEEE Ninth International Conference on Advanced Video and Signal-Based Surveillance.
[36] Christophe Rosenberger,et al. Abnormal events detection based on spatio-temporal co-occurences , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[37] Qixiang Ye,et al. Visual abnormal behavior detection based on trajectory sparse reconstruction analysis , 2013, Neurocomputing.
[38] Martin D. Levine,et al. An on-line, real-time learning method for detecting anomalies in videos using spatio-temporal compositions , 2013, Comput. Vis. Image Underst..
[39] Yoshua Bengio,et al. Gradient-based learning applied to document recognition , 1998, Proc. IEEE.
[40] Christian Bauckhage,et al. Loveparade 2010: Automatic video analysis of a crowd disaster , 2012, Comput. Vis. Image Underst..
[41] Nannan Li,et al. Spatio-temporal context analysis within video volumes for anomalous-event detection and localization , 2015, Neurocomputing.
[42] Guohui Li,et al. Unsupervised kernel learning for abnormal events detection , 2013, The Visual Computer.
[43] Ehud Rivlin,et al. Robust Real-Time Unusual Event Detection using Multiple Fixed-Location Monitors , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[44] Göran Falkman,et al. Online Learning and Sequential Anomaly Detection in Trajectories. , 2013, IEEE transactions on pattern analysis and machine intelligence.
[45] Dacheng Tao,et al. Slow Feature Analysis for Human Action Recognition , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[46] Lin Sun,et al. DL-SFA: Deeply-Learned Slow Feature Analysis for Action Recognition , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[47] Michael G. Strintzis,et al. Swarm Intelligence for Detecting Interesting Events in Crowded Environments , 2015, IEEE Transactions on Image Processing.
[48] Nuno Vasconcelos,et al. Anomaly Detection and Localization in Crowded Scenes , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[49] Mubarak Shah,et al. Chaotic invariants of Lagrangian particle trajectories for anomaly detection in crowded scenes , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[50] Stefanos Zafeiriou,et al. Learning Slow Features for Behaviour Analysis , 2013, 2013 IEEE International Conference on Computer Vision.
[51] Mubarak Shah,et al. Learning object motion patterns for anomaly detection and improved object detection , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[52] Nannan Li,et al. Video anomaly detection based on a hierarchical activity discovery within spatio-temporal contexts , 2014, Neurocomputing.
[53] Tieniu Tan,et al. A system for learning statistical motion patterns , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[54] Fei-Fei Li,et al. Online detection of unusual events in videos via dynamic sparse coding , 2011, CVPR 2011.
[55] Ramakant Nevatia,et al. Hierarchical abnormal event detection by real time and semi-real time multi-tasking video surveillance system , 2013, Machine Vision and Applications.
[56] Yee Whye Teh,et al. A Fast Learning Algorithm for Deep Belief Nets , 2006, Neural Computation.
[57] Louis Kratz,et al. Anomaly detection in extremely crowded scenes using spatio-temporal motion pattern models , 2009, CVPR.
[58] Anthony Hoogs,et al. Detecting rare events in video using semantic primitives with HMM , 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..
[59] Z. C. Liu,et al. Observation of vortex packets in direct numerical simulation of fully turbulent channel flow , 2002 .
[60] Bo Wang,et al. Abnormal crowd behavior detection using high-frequency and spatio-temporal features , 2011, Machine Vision and Applications.
[61] Alessio Del Bue,et al. Optimizing interaction force for global anomaly detection in crowded scenes , 2011, 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops).