Abnormal event detection in crowded scenes using sparse representation

Pattern Recognition

Volumn 46, Issue 7, 2013, Pages 1851-1864

  Cong, Yang ^a,b   Yuan, Junsong ^b   Liu, Ji ^c  

^a SHENYANG INSTITUTE OF AUTOMATION   (China)

^b NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

^c University of Wisconsin   (United States)

Author keywords

Abnormal event; Crowd analysis; Sparse representation; Video surveillance

Indexed keywords

ABNORMAL EVENT; ABNORMAL EVENT DETECTIONS; CROWD ANALYSIS; OBJECT DETECTION AND TRACKING; SPARSE REPRESENTATION; SPATIO-TEMPORAL PATCHES; STATE-OF-THE-ART METHODS; VIDEO SURVEILLANCE;

CONVEX OPTIMIZATION; SECURITY SYSTEMS;

ITERATIVE METHODS;

EID: 84875239530     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patcog.2012.11.021     Document Type: Article

References (39)

1. A. Adam, E. Rivlin, I. Shimshoni, and D. Reinitz Robust real-time unusual event detection using multiple fixed-location monitors IEEE Transactions on Pattern Analysis and Machine Intelligence 30 2008 555 560
2. S. Avidan Ensemble tracking IEEE Transactions on Pattern Analysis and Machine Intelligence 2007 261 271
3. Y. Benezeth, P. Jodoin, V. Saligrama, C. Rosenberger, Abnormal events detection based on spatio-temporal co-occurrences, in: CVPR, 2009.
4. O. Boiman, M. Irani, Detecting irregularities in images and in video, in: ICCV, 2005.
5. O. Boiman, and M. Irani Detecting irregularities in images and in video International Journal of Computer Vision 74 1 2007 17 31
6. Y. Cong, H. Gong, S. Zhu, Y. Tang, Flow mosaicking: real-time pedestrian counting without scene-specific learning, in: CVPR, 2009, pp. 1093-1100.
7. Y. Cong, J. Yuan, J. Liu, Sparse reconstruction cost for abnormal event detection, in: IEEE Conference on Computer Vision and Pattern Recognition, 2011, pp. 3449-3456.
8. N. Dalal, B. Triggs, Histograms of oriented gradients for human detection, in: CVPR, 2005, pp. 886-893.
9. D.P. Helbing Social force model for pedestrian dynamics Physical Review E 51 1995 4282
10. L. Ernesto, S.B. Andrade, R.B. Fisher, Modelling crowd scenes for event detection, in: ICPR, 2006.
11. 〈 http://www.svcl.ucsd.edu/projects/anomaly 〉 [n.d.].
12. W. Hu, X. Xiao, Z. Fu, D. Xie, T. Tan, and S. Maybank A system for learning statistical motion patterns IEEE Transactions on Pattern Analysis and Machine Intelligence 28 9 2006 1450 1464
13. K. Huang, S. Aviyente, Sparse representation for signal classification, in: NIPS, 2007.
14. L. Itti, P. Baldi, A principled approach to detecting surprising events in video, in: CVPR, 2005.
15. F. Jiang, J. Yuan, S. Tsaftaris, and A. Katsaggelos Anomalous video event detection using spatiotemporal context Computer Vision and Image Understanding 115 3 2011 323 333
16. J. Kim, K. Grauman, Observe locally, infer globally: a space-time MRF for detecting abnormal activities with incremental updates, in: CVPR, 2009.
17. L. Kratz, K. Nishino, Anomaly detection in extremely crowded scenes using spatio-temporal motion pattern models, in: CVPR, 2009.
18. H. Lee, A. Battle, R. Raina, and A. Ng Efficient sparse coding algorithms NIPS 19 2007 801
19. C. Liu, W. Freeman, E. Adelson, Y. Weiss, Human-assisted motion annotation, in: CVPR, 2008.
20. J. Liu, P. Musialski, P. Wonka, J. Ye, Tensor completion for estimating missing values in visual data, in: ICCV, 2009.
21. J. Liu, J. Liu, P. Wonka, and J. Ye Sparse non-negative tensor factorization using columnwise coordinate descent Pattern Recognition 45 1 2012 649 656
22. Y. Ma, H. Derksen, W. Hong, and J. Wright Segmentation of multivariate mixed data via lossy data coding and compression IEEE Transactions on Pattern Analysis and Machine Intelligence 29 9 2007 1546 1562
23. V. Mahadevan, W. Li, V. Bhalodia, N. Vasconcelos, Anomaly detection in crowded scenes, in: CVPR, 2010, pp. 1975-1981.
24. X. Mei, H. Ling, Robust visual tracking using l1 minimization, in: ICCV, IEEE, 2009, pp. 1436-1443.
25. B. Olshausen, and D. Field Sparse coding with an overcomplete basis set a strategy employed by v1? Vision Research 37 23 1997 3311 3325
26. B. Olshausen Emergence of simple-cell receptive field properties by learning a sparse code for natural images Nature 381 6583 1996 607 609
27. Ramin Mehran, M.S. Alexis Oyama, Abnormal crowd behavior detection using social force model, in: CVPR, 2009.
28. M.S. Saad Ali, Floor fields for tracking in high density crowd scenes, in: ECCV, 2008.
29. C. Stauffer, W. Grimson, Adaptive background mixture models for real-time tracking, in: CVPR, 2002.
30. I. Tziakos, A. Cavallaro, and L. Xu Event monitoring via local motion abnormality detection in non-linear subspace Neurocomputing 73 2010 1881 1891
31. Unusual crowd activity dataset of University of Minnesota, from 〈 http://mha.cs.umn.edu/movies/crowdactivity-all.avi 〉. [n.d.].
32. X. Wang, X. Ma, and W. Grimson Unsupervised activity perception in crowded and complicated scenes using hierarchical Bayesian models IEEE Transactions on Pattern Analysis and Machine Intelligence 31 3 2009 539 555
33. J. Wright, A. Yang, A. Ganesh, S. Sastry, and Y. Ma Robust face recognition via sparse representation IEEE Transactions on Pattern Analysis and Machine Intelligence 31 2 2008 210 227
34. S. Wu, B. Moore, M. Shah, Chaotic invariants of Lagrangian particle trajectories for anomaly detection in crowded scenes, in: CVPR, 2010.
35. W.A.J. Yu Modeling crowd turbulence by many-particle simulation Physical Review E 76 4 2007 046105
36. J. Yuan, Z. Liu, Y. Wu, Discriminative subvolume search for efficient action detection, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2009.
37. T. Zhang On the consistency of feature selection using greedy least squares regression The Journal of Machine Learning Research 10 2009 555 568
38. B. Zhao, L. Fei-Fei, E. Xing, Online detection of unusual events in videos via dynamic sparse coding, in: CVPR, 2011.
39. H. Zhong, J. Shi, M. Visontai, Detecting unusual activity in video, in: CVPR, 2004.