Learning pixel-wise signal energy for understanding semantics

Image and Vision Computing

Volumn 21, Issue 13-14, 2003, Pages 1183-1189

  Ng, Jeffrey ^a   Gong, Shaogang ^a  

^a QUEEN MARY UNIVERSITY OF LONDON   (United Kingdom)

Author keywords

Abnormal event detection; CONDENSATION based trajectory matching; Deviant event; Gaussian mixture models; Phase information; Quadrature filter pair

Indexed keywords

IMAGE ANALYSIS; IMAGE SEGMENTATION; LEARNING SYSTEMS; MATHEMATICAL MODELS; TRAJECTORIES;

ABNORMAL EVENT DETECTION; GAUSSIAN MIXTURE MODELS; PHASE INFORMATION;

SEMANTICS;

EID: 0344515602     PISSN: 02628856     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.imavis.2003.09.001     Document Type: Conference Paper

References (13)

1. Adelson E.H., Bergen J.R. The plenoptic function and the elements of early vision. In Computational Models of Visual Processing. 1991;MIT Press, Cambridge, MA.
2. Black M.J., Jepson A.D. A probabilistic framework for matching temporal trajectories: condensation-based recognition of gestures and expressions. In European Conference on Computer Vision, Freiburg. 1998;. pp. 909-924.
3. Chomat O., Crowley J. A probabilistic sensor for the perception and the recognition of activities. In European Conference on Computer Vision, Dublin. 2000;. pp. 487-503.
4. Freeman W.T., Adelson E.H. The design and use of steerable filters. IEEE PAMI. 13:(9):1991;891-906.
5. Gong S., Walter M., Psarrou A. Recognition of temporal structures: learning prior and propagating observation augmented densities via hidden Markov states. In IEEE International Conference on Computer Vision, Confu. 1999;. pp. 157-162.
6. Heeger D.J. Optical flow using spatiotemporal filters. International Journal of Computer Vision. 1:1987;279-302.
7. Isard M., Blake A. Contour tracking by stochastic propagation of conditional density. In European Conference on Computer Vision, Cambridge. 1996;. pp. 343-356.
8. Johnson N., Hogg D.C. Learning the distribution of object trajectories for event recognition. Image and Vision Computing. 14:(8):1996;609-615.
9. McKenna S.J., Jabri S., Duric Z., Wechsler H., Rosenfeld A. Tracking groups of people. Computer Vision and Image Understanding. 80:(1):2000;42-56.
10. Oppenheim A., Schafer R. Digital Signal Processing. 1975;Prentice-Hall, Englewood Cliffs, NJ.
11. Raja Y., McKenna S.J., Gong S. Tracking and segmenting people in varying lighting conditions using colour. In IEEE International Conference on Automatic Face and Gesture Recognition, Nara. 1998;. pp. 228-233.
12. Stauffer C., Grimson W.E.L. Using adaptive tracking to classify and monitor activities in a site. In IEEE Conference on Computer Vision and Pattern Recognition, Los Alamitos, USA. 1998;. pp. 22-29.
13. Usher M., Donnelly N. Visual synchrony affects binding and segmentation in perception. Letter to Nature. 394:1998;179-182.