An efficient subsequence search for video anomaly detection and localization

Multimedia Tools and Applications - Tập 75 Số 22 - Trang 15101-15122 - 2016
Kuo Hsing Cheng1, Yie‐Tarng Chen1, Wen‐Hsien Fang1
1Department of Electronic Engineering, National Taiwan University of Science and Technology, Taipei, Republic of China

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Tài liệu tham khảo

Adam A, Rivlin E, Shimshoni I, Reinitz D (2008) Robust real-time unusual event detection using multiple fixed-location monitors. IEEE Trans Pattern Anal Mach Intell 30:555–560

Antic B, Ommer B (2011) Video parsing for abnormality detection. In: Int. Conf. Comput. Vis., pp 2415–2422

Benezeth Y, Jodoin P, Saligrama V, Rosenberger C (2009) Abnormal events detection based on spatio-temporal co-occurences. In: Conf. Comput. Vis. Pattern Recognit., pp 2458–2465

Benezeth Y, Jodoin PM, Saligrama V (2011) Abnormality detection using low-level co-occurring events. Pattern Recognit Lett 32:423–431

Bertini M, Bimbo AD, Seidenari L (2012) Multi-scale and real-time non-parametric approach for anomaly detection and localization. Comput Vis Image Underst 116:320–329

Boiman O, Irani M (2005) Detecting irregularities in images and in video. In: Int. Conf. Comput. Vis., pp 462–469

Chandola V, Banerjee A, Kumar V (2009) Anomaly detection: a survey. ACM Comput Surv(CSUR) 41:41

Chen YT, Lin YC, Fang WH (2010) A video-based human fall detection system for the smart home. J Chin Eng 33:681–690

Cheng KW, Chen YT, Fang WH (2013) Abnormal crowd behavior detection and localization using maximum sub-sequence search. In: ACM/IEEE Int. Workshop Anal. Retr. Track. Event Motion Imag. Stream, pp 49–58

Cong Y, Yuan J, Liu J (2011) Sparse reconstruction cost for abnormal event detection. In: Conf. Comput. Vis. Pattern Recognit., pp 3449–3456

Dalal N, Triggs B (2005) Histograms of oriented gradients for human detection. In: Conf. Comput. Vis. Pattern Recognit., pp 886–893

Dalal N, Triggs B, Schmid C (2006) Human detection using oriented histograms of flow and appearance. In: Eur. Conf. Comput. Vis., pp 428–441

Duque D, Santos H, Cortez P (2007) Prediction of abnormal behaviors for intelligent video surveillance systems. In: Comput. Intell. Data Min., pp 362–367

Everingham M, Gool LV, Williams CKI, Winn J, Zisserman A (2010) The pascal visual object classes (voc) challenge. Int J Comput Vis 88:303–338

Fei-Fei L, Fergus R, Torralba A (2007) Recognizing and learning object categories. In: Antonio Torralba’s website http://people.csail.mit.edu/torralba/shortCourseRLOC/

Helbing D, Molnár P (1995) Social force model for pedestrian dynamics. Phys Rev E 51:4282–4286

Hu DH, Zhang X, Yin J, Zheng VW, Yang Q (2009) Abnormal activity recognition based on hdp-hmm models. In: Int. Jt. Conf. Artif. Intell., pp 1715–1720

Kettnaker VM (2003) Time-dependent hmms for visual intrusion detection. In: Comput. Vis. Pattern Recognit. Workshop, p 34

Kim J, Grauman K (2009) Observe locally, infer globally: A space-time mrf for detecting abnormal activities with incremental updates. In: Conf. Comput. Vis. Pattern Recognit., pp 2921–2928

Krüger V, Kragic D, Geib C (2007) The meaning of action: a review on action recognition and mapping. Adv Robot 21:1473–1501

Kwon J, Lee KM (2012) A unified framework for event summarization and rare event detection. In: Conf. Comput. Vis. Pattern Recognit., pp 1266–1273

LK, KN (2009) Anomaly detection in extremely crowded scenes using spatio-temporal motion pattern models. In: Conf. Comput. Vis. Pattern Recognit., pp 1446–1453

Lampert CH, Blaschko MB, Hofmann T (2008) Beyond sliding windows: Object localization by efficient subwindow search. In: Conf. Comput. Vis. Pattern Recognit., pp 1–8

Lee CK, Ho MF, Wen WS, Huang CL (2006) Abnormal event detection in video using n-cut clustering. In: J. Intell. Inf. Hiding Multimedia Signal Process., pp 407–410

Li W, Mahadevan V, Vasconcelos N (2013) Anomaly detection and localization in crowded scenes. IEEE Trans Pattern Anal Mach Intell 36:18–32

Lu C, Shi J, Jia J (2013) Abnormal event detection at 150 fps in matlab. In: Int. Conf. Comput. Vis

Mahadevan V, Li W, Bhalodia V, Vasconcelos N (2010) Anomaly detection in crowded scenes. In: Conf. Comput. Vis. Pattern Recognit., pp 1975–1981

Mehran R, Oyama A, Shah M (2009) Abnormal crowd behavior detection using social force model. In: Conf. Comput. Vis. Pattern Recognit., pp 935–942

Nater F, Grabner H, Van Gool L (2010) Exploiting simple hierarchies for unsupervised human behavior analysis. In: Conf. Comput. Vis. Pattern Recognit., pp 2014–2020

Popoola O, Wang K (2012) Video-based abnormal human behavior recognition xa review. IEEE Trans Syst Man Cybern Soc:865–878

Rohstkhari MJ, Levine MD (2013) Human activity recognition in videos using a single example. Image Vis Comput 31:864–876

Rohstkhari MJ, Levine MD (2013) Online dominant and anomalous behavior detection in videos. In: Conf. Comput. Vis. Pattern Recognit., pp 2611–2618

Rublee E, Rabaud V, Konolige K, Bradski GR (2011) Orb: An efficient alternative to sift or surf. In: Int. Conf. Comput. Vis., pp 2564–2571

Saligrama V, Chen Z (2012) Video anomaly detection based on local statistical aggregates. In: Conf. Comput. Vis. Pattern Recognit., pp 2112–2119

Scholkopt B, Platt J, Shawe-Taylor J, Smola A, Williamson R (2001) Estimating the support of a high-dimensional distribution. Neural Comput 13:1443–1471

Stauffer C, Grimson W (2000) Learning patterns of activity using real-time tracking. IEEE Trans Pattern Anal Mach Intell 22:747–757

Tran D, Yuan J (2011) Optimal spatio-temporal path discovery for video event detection. In: Conf. Comput. Vis. Pattern Recognit., pp 3321–3328

Tran D, Yang J, Forsyth D (2013) Video event detection: from subvolume localization to spatio-temporal path search. IEEE Trans Pattern Anal Mach Intell 36:404–416

Voulodimos AS, Kosmopoulos DI, Doulamis ND, Varvarigou TA (2014) A top-down event-driven approach for concurrent activity recognition. Multimed Tool Appl 69:293–311

Wang T, Snoussi H (2013) Histograms of optical flow orientation for abnormal events detection. In: IEEE Int. Workshop Perform. Eval. Track. Surveill., pp 45–52

Wiliem A, Madasu V, Boles W, Yarlagadda P (2008) Detecting uncommon trajectories. In: Digit. Image Comput. Tech. Appl., pp 398–404

Xiang T, Gong S (2008) Video behavior profiling for anomaly detection. IEEE Trans Pattern Anal Mach Intell 30:893–908

Yin J, Yang Q, Pan J (2008) Sensor-based abnormal human-activity detection. IEEE Trans Knowl Data Eng 20:1082–1090

Yuan J, Liu Z, Wu Y (2009) Discriminative subvolume search for efficient action detection. In: Conf. Comput. Vis. Pattern Recognit., pp 2442–2449

Zaharescu A, Wildes R (2010) Anomalous behaviour detection using spatiotemporal oriented energies, subset inclusion histogram comparison and event-driven processing. In: Eur. Conf. Comput. Vis., pp 563–576

Zhang D, Gatica-Perez D, Bengio S, McCowan I (2005) Semi-supervised adapted hmms for unusual event detection. In: Conf. Comput. Vis. Pattern Recognit., pp 611–618

Zivkovic Z (2004) Improved adaptive gaussian mixture model for background subtraction. In: Int. Conf. Pattern Recognit., pp 28–31