[1] Cong Y, Yuan J, Liu J. Sparse reconstruction cost for abnormal event detection. In Proc. IEEE Conference on Computer Vision and Pattern Recognition, June 2011, pp.3449- 3456.[2] Zhao B, Li F F, Xing E P. Online detection of unusual events in videos via dynamic sparse coding. In Proc. IEEE Conference on Computer Vision and Pattern Recognition, June 2011, pp.3313-3320.[3] Zhou Y, Bai X, Liu W et al. Swarm fusion for visual tracking. International Journal of Computer Vision, 2016, 118(3): 337-363.[4] Li C, Han Z, Ye Q, Jiao J. Abnormal behavior detection via sparse reconstruction analysis of trajectory. In Proc. the 6th International Conference on Image and Graphics, August 2011, pp.807-810.[5] Piciarelli C, Micheloni C, Foresti G L. Trajectory-based anomalous event detection. IEEE Transactions on Circuits and Systems for Video Technology, 2008, 18(11): 1544- 1554.[6] Lu X, Wang Y, Yuan Y. Alternatively constrained dictionary learning for image superresolution. IEEE Transactions on Cybernetics, 2014, 44(3): 366-377.[7] Mehran R, Oyama A, Shah M. Abnormal crowd behavior detection using social force model. In Proc. IEEE Conference on Computer Vision and Pattern Recognition, June 2009, pp.935-942.[8] Lu X, Yuan Y, Zheng X. Jointly dictionary learning for change detection in multispectral imagery. IEEE Transactions on Cybernetics, 2017, 47(4): 884-897.[9] Chandola V, Banerjee A, Kumar V. Anomaly detection: A survey. ACM Computing Surveys, 2009, 41(3): 15:1-15:58.[10] Vishwakarma S, Agrawal A. A survey on activity recognition and behavior understanding in video surveillance. The Visual Computer, 2013, 29(10): 983-1009.[11] Borges P V K, Conci N, Cavallaro A. Video-based human behavior understanding: A survey. IEEE Transactions on Circuits and Systems for Video Technology, 2013, 23(11): 1993-2008.[12] Bruckstein A, Donoho D, Elad M. From sparse solutions of systems of equations to sparse modeling of signals and images. SIAM Rev., 2009, 51(1): 34-81.[13] Lu X, Wu H, Yuan Y. Double constrained NMF for hyperspectral unmixing. IEEE Transactions on Geoscience and Remote Sensing, 2014, 52(5): 2746-2758.[14] Lu X, Wang Y, Yuan Y. Graph regularized low-rank representation for destriping of hyperspectral images. IEEE Transactions on Geoscience and Remote Sensing, 2013, 51(7-1): 4009-4018.[15] Song B, Li J, Mura M D, Li P, Plaza A, Bioucas-Dias J M, Benediktsson J A, Chanussot J. Remotely sensed image classification using sparse representations of morphological attribute profiles. IEEE Transactions on Geoscience and Remote Sensing, 2014, 52(8): 5122-5136.[16] Lu C, Shi J, Jia J. Abnormal event detection at 150 FPS in MATLAB. In Proc. IEEE International Conference on Computer Vision, December 2013, pp.2720-2727.[17] Mo X, Monga V, Bala R, Fan Z. Adaptive sparse representations for video anomaly detection. IEEE Transactions on Circuits and Systems for Video Technology, 2014, 24(4): 631-645.[18] Basharat A, Gritai A, Shah M. Learning object motion patterns for anomaly detection and improved object detection. In Proc. IEEE Conference on Computer Vision and Pattern Recognition, June 2008.[19] Yuan Y, Fang J, Wang Q. Online anomaly detection in crowd scenes via structure analysis. IEEE Transactions on Cybernetics, 2015, 45(3): 562-575.[20] Itti L, Baldi P. A principled approach to detecting surprising events in video. In Proc. IEEE Conference on Computer Vision and Pattern Recognition, June 2005, pp.631-637.[21] Han J, Zhang D, Hu X, Guo L, Ren J, Wu F. Background prior-based salient object detection via deep reconstruction residual. IEEE Trans. Circuits and Systems for Video Technology, 2015, 25(8): 1309-1321.[22] Han J, Zhang D, Wen S, Guo L, Liu T, Li X. Two-stage learning to predict human eye fixations via SDAEs. IEEE Trans. Cybernetics, 2016, 46(2): 487-498.[23] Qi W, Cheng M, Borji A, Lu H, Bai L. SaliencyRank: Twostage manifold ranking for salient object detection. Computational Visual Media, 2016, 1(4): 309-320.[24] Cheng M, Mitra N J, Huang X, Torr P H S, Hu S. Global contrast based salient region detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015, 37(3): 569-582.[25] Boiman O, Irani M. Detecting irregularities in images and in video. International Journal of Computer Vision, 2007, 74(1): 17-31.[26] Kratz L, Nishino K. Anomaly detection in extremely crowded scenes using spatio-temporal motion pattern models. In Proc. IEEE Conference on Computer Vision and Pattern Recognition, June 2009, pp.1446-1453.[27] Wu S, Moore B, Shah M. Chaotic invariants of Lagrangian particle trajectories for anomaly detection in crowded scenes. In Proc. IEEE Conference on Computer Vision and Pattern Recognition, June 2010, pp.2054-2060.[28] Cheng H Y, Hwang J N. Integrated video object tracking with applications in trajectory-based event detection. Journal of Visual Communication and Image Representation, 2011, 22(7): 673-685.[29] Cui X, Liu Q, Gao M, Metaxas D N. Abnormal detection using interaction energy potentials. In Proc. the 24th IEEE Conference on Computer Vision and Pattern Recognition, June 2011, pp.3161-3167.[30] Saligrama V, Chen Z. Video anomaly detection based on local statistical aggregates. In Proc. IEEE Conference on Computer Vision and Pattern Recognition, June 2012, pp.2112-2119.[31] Popoola O P, Wang K. Video-based abnormal human behavior recognition - A review. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, 2012, 42(6): 865-878.[32] Sodemann A A, Ross M P, Borghetti B J. A review of anomaly detection in automated surveillance. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, 2012, 42(6): 1257-1272.[33] Li T, Chang H, Wang M, Ni B, Hong R, Yan S. Crowded scene analysis: A survey. IEEE Transactions on Circuits and Systems for Video Technology, 2015, 25(3): 367-386.[34] Zhong H, Shi J, Visontai M. Detecting unusual activity in video. In Proc. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Volume 2, June 27-July 2, 2004, pp.819-826.[35] Benezeth Y, Jodoin P M, Saligrama V, Rosenberger C. Abnormal events detection based on spatio-temporal cooccurences. In Proc. IEEE Conference on Computer Vision and Pattern Recognition, June 2009, pp.2458-2465.[36] del Rincon J, Lewandowski M, Nebel J C, Makris D. Generalized Laplacian eigenmaps for modeling and tracking human motions. IEEE Transactions on Cybernetics, 2014, 44(9): 1646-1660.[37] Azhar F, Tjahjadi T. Significant body point labeling and tracking. IEEE Transactions on Cybernetics, 2014, 44(9): 1673-1685.[38] Xie Y, Zhang W, Li C, Lin S, Qu Y, Zhang Y. Discriminative object tracking via sparse representation and online dictionary learning. IEEE Transactions on Cybernetics, 2014, 44(4): 539-553.[39] Yang Y, Hu W, Xie Y, Zhang W, Zhang T. Temporal restricted visual tracking via reverse-low-rank sparse learning. IEEE Transactions on Cybernetics, 2016, 47(2): 485-498.[40] Zhang Y, Chen X, Lin L, Xia C, Zou D. High-level representation sketch for video event retrieval. Science in China Series F: Information Sciences, 2016, 59(7): 072103.[41] Adam A, Rivlin E, Shimshoni I, Reinitz D. Robust real-time unusual event detection using multiple fixed-location monitors. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2008, 30(3): 555-560.[42] Kim J, Grauman K. Observe locally, infer globally: A spacetime MRF for detecting abnormal activities with incremental updates. In Proc. IEEE Conference on Computer Vision and Pattern Recognition, June 2009, pp.2921-2928.[43] Mahadevan V, Li W, Bhalodia V, Vasconcelos N. Anomaly detection in crowded scenes. In Proc. the 23rd IEEE Conference on Computer Vision and Pattern Recognition, June 2010, pp.1975-1981.[44] Li W, Mahadevan V, Vasconcelos N. Anomaly detection and localization in crowded scenes. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2014, 36(1): 18-32.[45] Cong Y, Yuan J, Liu J. Abnormal event detection in crowded scenes using sparse representation. Pattern Recognition, 2013, 46(7): 1851-1864.[46] Thida M, Eng H L, Remagnino P. Laplacian eigenmap with temporal constraints for local abnormality detection in crowded scenes. IEEE Transactions on Cybernetics, 2013, 43(6): 2147-2156.[47] Kaltsa V, Briassouli A, Kompatsiaris I, Hadjileontiadis L J, Strintzis M G. Swarm intelligence for detecting interesting events in crowded environments. IEEE Transactions on Image Processing, 2015, 24(7): 2153-2166.[48] Reddy V, Sanderson C, Lovell B C. Improved anomaly detection in crowded scenes via CellBased analysis of foreground speed, size and texture. In Proc. IEEE Conference on Computer Vision and Pattern Recognition, June 2011, pp.55-61.[49] Censor Y, Zenios S. Parallel optimization: Theory, algorithms and applications. Oxford University Press, 1997. |