-
2
-
-
84995309325
-
-
F. Marquis-Faulkes, S.J. McKenna, P. Gregor, A.F. Newell, Scenario-based drama as a tool for investigating user requirements with application to home monitoring for elderly people, in: HCI International, vol. 3, Crete, Greece, 2003, pp. 512-516.
-
-
-
-
3
-
-
84957604139
-
-
M. Isard, A. Blake, Contour tracking by stochastic propagation of conditional density, in: European Conference on Computer Vision, vol. 1, 1996, pp. 343-356.
-
-
-
-
4
-
-
0027580559
-
Novel approach to nonlinear and non-Gaussian Bayesian state estimation
-
Gordon N., Salmond D., and Smith A.F.M. Novel approach to nonlinear and non-Gaussian Bayesian state estimation. IEE Proceedings-F 140 (1993) 107-113
-
(1993)
IEE Proceedings-F
, vol.140
, pp. 107-113
-
-
Gordon, N.1
Salmond, D.2
Smith, A.F.M.3
-
5
-
-
84957655116
-
-
M. Isard, A. Blake, Icondensation: unifying low-level and high-level tracking in a stochastic framework, in: European Conference on Computer Vision, vol. I, Freiburg, Germany, 1998, pp. 893-908.
-
-
-
-
6
-
-
84995302661
-
-
D. Tweed, A. Calway, Tracking many objects using subordinated condensation, in: Proceedings of the British Machine Vision Conference, 2002, pp. 283-292.
-
-
-
-
7
-
-
0007997129
-
-
O. King, D.A. Forsyth, How does Condensation behave with a finite number of samples?, in: European Conference on Computer Vision, 2000, pp. 695-709.
-
-
-
-
8
-
-
0035691549
-
-
Y. Rui, Y. Chen, Better proposal distributions: object tracking using unscented particle filter, in: IEEE Conference on Computer Vision and Pattern Recognition, Hawaii, 2001, pp. 786-793.
-
-
-
-
9
-
-
84995337313
-
-
P. Li, T. Zhang, Visual contour tracking based on particle filters, in: First International Workshop on Generative-Model-Based Vision, 2002, pp. 61-70.
-
-
-
-
10
-
-
0034857313
-
-
K. Choo, D.J. Fleet, People tracking using hybrid Monte Carlo filtering, in: IEEE International Conference on Computer Vision, Vancouver, 2001, pp. 321-328.
-
-
-
-
11
-
-
0033697160
-
-
J. Deutscher, A. Blake, I. Reid, Articulated body motion capture by annealed particle filtering, in: IEEE Conference on Computer Vision and Pattern Recognition, vol. 2, South Carolina, USA, 2000, pp. 126-133.
-
-
-
-
12
-
-
0035696550
-
-
J. Deutscher, A. Davison, I. Reid, Automatic partitioning of high dimensional search spaces associated with articulated body motion capture, in: IEEE Conference on Computer Vision and Pattern Recognition, vol. 2, Hawaii, 2001, pp. 669-676.
-
-
-
-
13
-
-
0032627094
-
-
T. Cham, J.M. Rehg, A multiple hypothesis approach to figure tracking, in: IEEE Conference on Computer Vision and Pattern Recognition, vol. VII, Fort Collins, 1998, pp. 239-245.
-
-
-
-
14
-
-
84995361666
-
-
P. Torma, C. Szepesvri, LS-N-IPS: an improvement of particle filters by means of local search, in: 5th IFAC Symposium on Non-linear Control Systems, 2001, pp. 715-719.
-
-
-
-
15
-
-
0036606060
-
Detecting lameness using 're-sampling condensation' and 'multi-stream cyclic hidden Markov models'
-
Magee D.R., and Boyle R.D. Detecting lameness using 're-sampling condensation' and 'multi-stream cyclic hidden Markov models'. Image and Vision Computing 20 (2002) 581-594
-
(2002)
Image and Vision Computing
, vol.20
, pp. 581-594
-
-
Magee, D.R.1
Boyle, R.D.2
-
17
-
-
0003345004
-
Improving regularised particle filters
-
Doucet A., de Freitas J.F.G., and Gordon N.J. (Eds), Springer-Verlag, New York
-
Musso C., Oudjane N., and LeGland F. Improving regularised particle filters. In: Doucet A., de Freitas J.F.G., and Gordon N.J. (Eds). Sequential Monte Carlo Methods in Practice (2001), Springer-Verlag, New York 247-271
-
(2001)
Sequential Monte Carlo Methods in Practice
, pp. 247-271
-
-
Musso, C.1
Oudjane, N.2
LeGland, F.3
-
18
-
-
0000417862
-
Mixture models, Monte Carlo, Bayesian updating and dynamic models
-
West M. Mixture models, Monte Carlo, Bayesian updating and dynamic models. Computing Science and Statistics 24 (1993) 325-333
-
(1993)
Computing Science and Statistics
, vol.24
, pp. 325-333
-
-
West, M.1
-
19
-
-
0036475447
-
A tutorial on particle filters for on-line nonlinear/non-Gaussian Bayesian tracking
-
Arulampalam S., Maskell S.R., Gordon N.J., and Clapp T. A tutorial on particle filters for on-line nonlinear/non-Gaussian Bayesian tracking. IEEE Transactions on Signal Processing 50 2 (2002) 174-188
-
(2002)
IEEE Transactions on Signal Processing
, vol.50
, Issue.2
, pp. 174-188
-
-
Arulampalam, S.1
Maskell, S.R.2
Gordon, N.J.3
Clapp, T.4
-
20
-
-
84995361660
-
-
K. Nummiaro, E. Koller-Meier, L. Van Gool, A color-based particle filter, in: A. Pece (Ed.), First International Workshop on Generative-Model-Based Vision, vol. 2002/01, 2002, pp. 53-60.
-
-
-
-
21
-
-
0027676791
-
A framework for spatio-temporal control in the tracking of visual contours
-
Blake A., Curwen R., and Zisserman A. A framework for spatio-temporal control in the tracking of visual contours. International Journal of Computer Vision 11 2 (1993) 127-145
-
(1993)
International Journal of Computer Vision
, vol.11
, Issue.2
, pp. 127-145
-
-
Blake, A.1
Curwen, R.2
Zisserman, A.3
-
22
-
-
84995361661
-
-
M. Walter, A. Psarrou, S. Gong, Learning prior and observation augmented density models for behaviour recognition, in: British Machine Vision Conference, Nottingham, 1999, pp. 23-32.
-
-
-
-
23
-
-
0036059551
-
-
N. Vlassis, B. Terwijn, B. Krose, Auxiliary particle filter robot localization from high-dimensional sensor observations, in: IEEE International Conference on Robotics and Automation, Washington, DC, 2002, pp. 7-12.
-
-
-
-
24
-
-
0036475565
-
Particle filters for positioning, navigation and tracking
-
Gustafsson F., Gunnarsson F., Bergman N., Forssell U., Jansson J., Karlsson R., and Nordlund P.-J. Particle filters for positioning, navigation and tracking. IEEE Transactions on Signal Processing 50 2 (2002) 425-437
-
(2002)
IEEE Transactions on Signal Processing
, vol.50
, Issue.2
, pp. 425-437
-
-
Gustafsson, F.1
Gunnarsson, F.2
Bergman, N.3
Forssell, U.4
Jansson, J.5
Karlsson, R.6
Nordlund, P.-J.7
-
25
-
-
84958960772
-
The bias-variance dilemma of the Monte Carlo method
-
Dorffner G., Bischof H., and Hornik K. (Eds), Springer Verlag
-
Zlochin M., and Baram Y. The bias-variance dilemma of the Monte Carlo method. In: Dorffner G., Bischof H., and Hornik K. (Eds). Artificial Neural Networks: ICANN (2001), Springer Verlag 141-147
-
(2001)
Artificial Neural Networks: ICANN
, pp. 141-147
-
-
Zlochin, M.1
Baram, Y.2
-
26
-
-
84995361662
-
-
T. Roberts, S.J. McKenna, I.W. Ricketts, Adaptive learning of statistical appearance models for 3D human tracking, in: British Machine Vision Conference, Cardiff, 2002, pp. 333-342.
-
-
-
-
27
-
-
0032302833
-
-
S. Birchfield, Elliptical head tracking using intensity gradients and color histograms, in: IEEE Conference on Computer Vision and Pattern Recognition, Santa Barbara, CA, 1998, pp. 232-237.
-
-
-
|