Human behaviour profiling for anomaly detection

Emerald - Tập 4 Số 3 - Trang 366-379 - 2011
XudongZhu1, Zhi‐JingLiu1
1School of Computer Science and Technology, Xidian University, Xi’an, China

Tóm tắt

PurposeThe purpose of this paper is to address the problem of profiling human behaviour patterns captured in surveillance videos for the application of online normal behaviour recognition and anomaly detection.Design/methodology/approachA novel framework is developed for automatic behaviour profiling and online anomaly detection without any manual labeling of the training dataset.FindingsExperimental results demonstrate the effectiveness and robustness of the authors' approach using noisy and sparse datasets collected from one real surveillance scenario.Originality/valueTo discover the topics, co‐clustering topic model not only captures the correlation between words, but also models the correlations between topics. The major difference between the conventional co‐clustering algorithms and the proposed CCMT is that CCMT shows a major improvement in terms of recall, i.e. interpretability.

Từ khóa


Tài liệu tham khảo

Abbes, T., Bouhoula, A. and Rusinowitch, M. (2004), “Protocol analysis in intrusion detection using decision tree”, Proc. Int. Conf. Inf. Technol.: Coding Comput., Vol. 1, pp. 404‐8.

Asaka, M., Onabura, T., Inoue, T. and Goto, S. (2002), “Remote attack detection method in IDA: MLSI‐based intrusion detection using discriminant analysis”, Proc. Symp. Appl. Internet, Nara, Japan, pp. 64‐73.

Blei, D.M., Ng, A.Y. and Jordan, M.I. (2003), “Latent Dirichlet allocation”, Journal of Machine Learning Research, Vol. 1, pp. 993‐1022.

Boiman, O. and Irani, M. (2005), “Detecting irregularities in images and in video”, Proc. IEEE International Conference on Computer Vision, Beijing, China, pp. 462‐9.

Bonifacio, J.M., Cansian, A.M., De Carvalho, A.C.P.L.F. and Moreira, E.S. (1998), “Neural networks applied in intrusion detection systems”, Proc. IEEE Int. Joint Conf. Neural Netw., Vol. 1, pp. 205‐10.

Dollar, P., Rabaud, V. and Cottrell, G. (2005), “Behavior recognition via sparse spatio‐temporal features”, Proc. 2nd Joint IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance, Beijing, China, pp. 65‐72.

Fanti, C., Zelnik‐Manor, L. and Perona, P. (2005), “Hybrid models for human motion recognition”, Proc. the Tenth IEEE International Conference on Computer Vision, Beijing, China, pp. 1166‐73.

Hamid, R., Johnson, A., Batta, S., Bobick, A., Isbell, C. and Coleman, G. (2005), “Detection and explanation of anomalous activities: representing activities as bags of event n‐grams”, Proc. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Beijing, China, pp. 1031‐8.

Lucas, B.D. and Kanade, T. (1981), “An iterative image registration technique with an application to stereo vision”, International Joint Conference on Artificial Intelligence, Vancouver, BC, Canada, pp. 674‐9.

Mukkamala, S., Janoski, G. and Sung, A.H. (2002), “Intrusion detection using neural networks and support vector machines”, Proc. Int. Joint Conf. Neural Netw., Vol. 2, pp. 1702‐7.

Niebles, J.C., Wang, H. and Fei‐Fei, L. (2008), “Unsupervised learning of human action categories using spatial‐temporal words”, International Journal of Computer Vision, Vol. 79 No. 3, pp. 299‐318.

Schuldt, C., Laptev, I. and Caputo, B. (2004), “Recognizing human actions: a local SVM approach”, Proc. ICPR, Cambridge, MA, USA, pp. 32‐6.

Shafiei, M.M. and Milios, E.E. (2006), “Latent Dirichlet co‐clustering”, Proc. the Sixth International Conference on Data Mining, Bethesda, MD, USA, pp. 18‐23.

Shimada, A., Kanouchi, M., Arita, D. and Taniguchi, R. (2008), “Robust human posture analysis using incremental learning and recall based on degree of confidence of feature points”, International Journal of Intelligent Computing and Cybernetics, Vol. 2 No. 2, pp. 304‐26.

Song, Y., Goncalves, L. and Perona, P. (2003), “Unsupervised learning of human motion”, IEEE Trans. Pattern Analysis and Machine Intelligence, Vol. 25 No. 7, pp. 814‐27.

Sung, A.H. and Mukkamala, S. (2003), “Identifying important features for intrusion detection using support vector machines and neural networks”, Proc. Symp. Appl. Internet, Washington, DC, USA, pp. 209‐16.

Xiang, T. and Gong, S. (2008), “Video behaviour profiling for anomaly detection”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 30, pp. 893‐908.

Yilmaz, A. and Shah, M. (2005), “Recognizing human actions in videos acquired by un‐calibrated moving cameras”, Proc. the Tenth IEEE International Conference on Computer Vision, Beijing, China, pp. 150‐7.

Zhong, H., Shi, J. and Visontai, M. (2004), “Detecting unusual activity in video”, Proc. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Washington, DC, USA, pp. 819‐26.

Thông tin
Thông tin xuất bản

Emerald

Tập 4 Số 3

366-379

Thông tin tác giả