Video event segmentation and visualisation in non-linear subspace

Pattern Recognition Letters

Volumn 30, Issue 2, 2009, Pages 123-131

  Tziakos, Ioannis ^a   Cavallaro, Andrea ^a   Xu, Li Qun ^b  

^a QUEEN MARY UNIVERSITY OF LONDON   (United Kingdom)

^b MARTLESHAM HEATH   (United Kingdom)

Author keywords

Dimensionality reduction; Laplacian eigenmaps; Unusual event detection

Indexed keywords

FACE RECOGNITION; LAPLACE TRANSFORMS; MOTION ESTIMATION; PHOTOGRAPHY; VIDEO RECORDING;

DIMENSIONAL SPACES; DIMENSIONALITY REDUCTION; DIMENSIONALITY REDUCTIONS; GRAPH BASED; LAPLACIAN EIGENMAPS; LINEAR DIMENSIONALITIES; LINEAR SUBSPACES; MAXIMUM VARIANCES; MULTI-DIMENSIONAL; OBJECT TRACKING; PRINCIPAL COMPONENTS; RAW DATUMS; TEMPORAL INFORMATIONS; TEST SEQUENCES; TRAFFIC SURVEILLANCES; UNUSUAL EVENT DETECTION; VIDEO EVENT DETECTIONS; VIDEO EVENTS; VIDEO SEQUENCES; VISUALISATION;

PRINCIPAL COMPONENT ANALYSIS;

EID: 56049108387     PISSN: 01678655     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patrec.2008.02.028     Document Type: Article

References (19)

1. Belkin M., and Niyogi P. Laplacian eigenmaps for dimensionality reduction and data representation. Neural Comput. 15 6 (2003) 1373-1396
2. Boiman, O., Irani, M., 2005. Detecting irregularities in images and in video. In: Proc. 10th IEEE Internat. Conf. on Computer Vision, vol. 1, pp. 462-469.
3. Borchers, B., 1997. CSDP: AC library for semidefinite programming. Tech. Rep., Socorro NM, USA.
4. Hamid, R., Maddi, S., Bobick, A., Essa, I., 2006. Unsupervised analysis of activity sequences using event-motifs. In: Proc. 4th ACM Internat. Workshop on Video Surveillance and Sensor Networks, pp. 71-78.
5. Johnson N., and Hogg D. Learning the distribution of object trajectories for event recognition. Image Vision Comput. 14 8 (1996) 609-615
6. Li, Z., Li, Z., Gao, L., Katsaggelos, A., 2006. Locally embedded linear subspaces for efficient video indexing and retrieval. In: Proc. IEEE Internat. Conf. on Multimedia and Expo, pp. 1765-1768.
7. Mecocci, A., Pannozzo, M., Fumarola, A., 2003. Automatic detection of anomalous behavioural events for advanced real-time video surveillance. In: Proc. IEEE Internat. Symposium on Computational Intelligence for Measurement Systems and Applications, pp. 187-192.
8. Piciarelli C., and Foresti G. On-line trajectory clustering for anomalous events detection. Pattern Recognition Lett. 27 15 (2006) 1835-1842
9. Porikli, F., Haga, T., 2004. Event detection by eigenvector decomposition using object and frame features. In: Proc. Conf. on Computer Vision and Pattern Recognition Workshop, p. 114.
10. Roweis S.T., and Saul L.K. Nonlinear dimensionality reduction by locally linear embedding. Science 290 5500 (2000) 2323-2326
11. Shi J., and Malik J. Normalized cuts and image segmentation. IEEE Trans. Pattern Anal. Machine Intell. 22 8 (2000) 888-905
12. Skubic, M., 2005. Assessing mobility and cognitive problems in elders. In: AAAI Fall Symposium, Workshop on Caring Machines, AI in Eldercare.
13. Tenenbaum J.B., de Silva V., and Langford J.C. A global geometric frame-work for nonlinear dimensionality reduction. Science 290 5500 (2000) 2319-2323
14. Valera, M., Velastin, S., 2005. Intelligent distributed surveillance systems: A review. In: IEE Proc. Vision, Image and Signal Processing, vol. 152, p. 192-204.
15. Weinberger K.Q., and Saul L.K. Unsupervised learning of image manifolds by semidefinite programming. Internat. J. Comput. Vision 70 1 (2006) 77-90
16. Xiang, T., Gong, S., 2005. Relevance learning for spectral clustering with applications on image segmentation and video behaviour profiling. In: Proc. IEEE Conf. on Advanced Video and Signal Based Surveillance, pp. 28-33.
17. Xu, L.-Q., Luo, B., 2007. Appearance-based video clustering in 2D locality preserving projection subspace. In: Proc. 6th ACM Internat. Conf. on Image and Video Retrieval, p. 356-362.
18. Zhang, D., Gatica-Perez, D., Bengio, S., McCowan, I., 2005. Semi-supervised adapted HMMs for unusual event detection. In: Proc. IEEE Comput. Soc. Conf. on Computer Vision and Pattern Recognition, vol. 1, pp. 611-618.
19. Zhong, H., Shi, J., Visontai, M., 2004. Detecting unusual activity in video. In: Proc. IEEE Comput. Soc. Conf. on Computer Vision and Pattern Recognition, vol. 2, pp. 819-826.