People trajectory mining with statistical pattern recognition

2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010

Volumn , Issue , 2010, Pages 1-8

  Calderara, Simone ^a   Cucchiara, Rita ^a  

^a UNIVERSITY OF MODENA AND REGGIO EMILIA   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

APPLICATION CONTEXTS; COMPLEX ENVIRONMENTS; INTEGRATED SOLUTIONS; NON-IDEALITIES; SIMILARITY MEASURE; SOCIAL ENVIRONMENT; SOCIAL INTERACTIONS; STATISTICAL FRAMEWORK; STATISTICAL PATTERN RECOGNITION; VIDEO-SURVEILLANCE;

COMPUTER VISION; TECHNICAL PRESENTATIONS;

TRAJECTORIES;

EID: 77956529441     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPRW.2010.5543158     Document Type: Conference Paper

References (15)

1. Y. Agiomyrgiannakis and Y. Stylianou. Stochastic modeling and quantization of harmonic phases in speech using wrapped gaussian mixture models. In Proc. of Intl Conf. on Acoustics, Speech and Signal Processing, pages IV: 1121-1124, 2007
2. C. Bahlmann. Directional features in online handwriting recognition. Pattern Recognition, 39:115-125, 2006
3. A. Basharat, A. Gritai, and M. Shah. Learning object motion patterns for anomaly detection and improved object detection. In Proc. of IEEE Int'l Conference on Computer Vision and Pattern Recognition, 2008
4. F. Bashir, A. Khokhar, and D. Schonfeld. A hybrid system for affine-invariant trajectory retrieval. In MIR '04: Proceedings of the 6th ACM SIGMM international workshop on Multimedia information retrieval, pages 235-242, New York, NY, USA, 2004. ACM
5. S. Calderara, A. Prati, and R. Cucchiara. HECOL: Homography and Epipolar-based Consistent Labeling for Outdoor Park Surveillance. in press on Computer Vision and Image Understanding
6. S. Calderara, A. Prati, and R. Cucchiara. Learning people trajectories using semi-directional statistics. In Proceedings of IEEE International Conference on Advanced Video and Signal Based Surveillance (IEEE AVSS 2009), Genova, Italy, Sept. 2009
7. H. Holzmann, A. Munk, M. Suster, and W. Zucchini. Hidden markov models for circular and linear-circular time series. Environmental and Ecological Statistics, 13(3):325-347, 2006
8. W. Hu, X. Xiao, Z. Fu, D. Xie, T. Tan, and S. Maybank. A system for learning statistical motion patterns. IEEE Trans. on PAMI, 28(9):1450-1464, September 2006
9. E. J. Keogh and M. J. Pazzani. Scaling up dynamic time warping for datamining application. In Proc. of ACM SIGKDD International Conference on Knowledge Discovery and Data mining (KDD 2000), pages 285-289, 2000
10. K. Mardia and P. Jupp. Directional Statistics. Wiley, 2000
11. B. Morris and M. Trivedi. A survey of vision-based trajectory learning and analysis for surveillance. IEEE Transactions on Circuits and Systems for Video Technology, 18(8):1114-1127, Aug. 2008
12. S. Needleman and C. Wunsch. A general method applicable to the search for similarities in the amino acid sequence of two proteins. Journal of Molecular Biology, 48(3):443-453, 1970
13. N. Piotto, N. Conci, and F. De Natale. Syntactic matching of trajectories for ambient intelligence applications. IEEE Transactions on Multimedia, 11(7):1266-1275, Nov. 2009
14. F. Porikli and T. Haga. Event detection by eigenvector decomposition using object and frame features. In Proc. of Computer Vision and Pattern Recognition (CVPR) Workshop, volume 7, pages 114-121, 2004
15. A. Prati, S. Calderara, and R. Cucchiara. Using circular statistics for trajectory analysis. In Proceedings of International Conference on Computer Vision and Pattern Recognition (CVPR 2008), June 2008