Spatiotemporal energy-based method for velocity estimation

Signal Processing

Volumn 65, Issue 3, 1998, Pages 347-362

  Spinei, Adrian ^a   Pellerin, Denis ^a,b   Hérault, Jeanny ^a,b  

^a GRENOBLE INSTITUTE OF TECHNOLOGY   (France)

^b UNIV GRENOBLE ALPES   (France)

Author keywords

Energy based methods; Motion estimation; Optical flow; Recursive Gabor filter

Indexed keywords

NUMERICAL METHODS; OBJECT RECOGNITION; OPTICAL FLOWS; SIGNAL FILTERING AND PREDICTION;

GABOR FILTERS;

IMAGE ANALYSIS;

EID: 0032025746     PISSN: 01651684     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0165-1684(97)00231-4     Document Type: Article

References (19)

1. J.L. Barron, D.J. Fleet, S.S. Beauchemin, Performances of optical flow techniques, Proc. Conf. on Computer Vision and Pattern Recognition, Champaign, June 1992, pp. 236-242.
2. J.L. Barron, D.J. Fleet, S.S. Beauchemin, Performances of optical flow techniques, Internat. J. Comput. Vision 12 (1) (1994) 43-77.
3. G.H. Donohoe, D.R. Hush, N. Ahmed, Change detection for target detection and classification in video sequences, Proc. Internat. Conf. Acoust. Speech Signal Process., New York, 1988, pp. 1084-1087.
4. D.J. Fleet, A.D. Jepson, Computation of component image velocity from local phase information, Internat. J. Comput. Vision 5 (1) (1990) 77-104.
5. S. Geman, D. Geman, C. Graffigne, P. Dong, Boundary detection by constrained optimization, IEEE Trans. Pattern Anal. Mach. Intell. 12 (1990) 609-628.
6. D.J. Heeger, Model for the extraction of image flow, J. Opt. Soc. Amer. A. 4 (8) (1987) 1455-1471.
7. F. Heitz, P. Bouthemy, Multimodal estimation of discontinuous optical flow using Markov random fields, IEEE Trans. Pattern Anal. Mach. Intell. 15 (12) (1993) 1217-1232.
8. R.A. Holub, M. Morton-Gibson, Response of visual cortical neurons of the cat to moving sinusoidal gratings: Response-contrast functions and spatiotemporal integration, J. Neurophysiol. 46 (1981) 1244-1259.
9. S.L. Iu, Robust estimation of motion vectors fields with discontinuity and occlusion using local outliers rejection, J. Visual Commun. Image Representation 6 (2) (1995) 132-141.
10. R. S. Jasinschi, Energy filters, motion uncertainty, and motion sensitive cells in the visual cortex: a mathematical analysis, Biol. Cybernet. 65 (1991) 515-523.
11. R. S. Jasinschi, Intrinsic constraints in space-time filtering: a new approach to representing uncertainty in low level vision, IEEE Trans. Pattern Anal. Mach. Intell. 14 (3) (1992) 353-366.
12. J.M. Jolion, A. Rosenfeld, A Pyramid Framework for Early Vision, Kluwer Academic Publishers, Dordrecht, 1994.
13. J. Konrad, E. Dubois, Bayesian estimation of motion vector fields, IEEE Trans. Pattern Anal. Mach. Intell. 14 (9) (1992) 910-927.
14. J.M. Létang, V. Rebuffel, P. Bouthemy, Motion detection robust to perturbations: A statistical regularization and temporal integration framework, Proc. 4th Internat. Conf. on Computer Vision, Berlin, 1993, pp. 21-30.
15. A. Mitiche, P. Bouthemy, Computation and analysis of image motion: a synopsis of current problems and methods, Internat. J. Comput. Vision 19 (1) (1996) 29-55.
16. H.H. Nagel, G. Socher, H. Kollnig, M. Otte, Motion boundary detection in image sequences by local stochastic tests, Proc. 3rd European Conf. on Computer Vision, Stockholm, 1994, pp. 305-315.
17. M. Unser, Fast Gabor-like windowed Fourier and continuous wavelet transforms, NCCR Report 143/93, National Institutes of Health, 1993.
18. J. Wiklund, G.H. Granlund, Image sequence analysis for object tracking, Proc. 5th Scandinavian Conf. on Image Analysis, 1987, pp. 641-648.
19. I.A. Young, L.J. van Vliet, Recursive implementation of the Gaussian filter, Signal Processing 44 (1995) 139-151.