D. Terzopoulos and R. Szeliski. Tracking with Kalman snakes. In A. Blake, editor, Active Vision, chapter 1, pages 3--20. MIT Press, 1992. Home/Search Document Not in Database Summary Related Articles Check |
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Tracking Non-Rigid Objects Using Functional Distance Metric - Laskov, Kambhamettu (Correct)
.... objects is that of physics based deformable models, introduced in [11] It has been widely used for tracking of 3D objects and for non rigid motion modeling [4] 5] 17] Coupled with the Kalman filtering approach, this method has been extended to handle complex motions of non rigid objects [15] [16]. However the physics based methods require knowledge of certain physical properties of the bodies in question, which are not always available. Some approaches ( 1] 6] 7] estimate the model properties using a set of cue points manually chosen at initialization stage. In reallife applications ....
Demetri Terzopoulos and Richard Szeliski. Tracking with Kalman snakes. In Blake and Yuille [3], pages 3--20.
Active Contours for Tracking Distributions - Freedman (2002) (Correct)
....length shortly, demonstrates the ability of such trackers to succeed. The active contour literature is vast, so no attempt will be made to review it comprehensively. The field originated with the snake formulation of Kass, Witkin, and Terzopoulos [8] and many papers in a similar vein followed [1, 17, 19]. The recent trend has been towards geometric curve evolution [3, 9, 10, 4] and this paper will follow in that tradition. Many of these recent papers have focused on the novel level set approach to implementing geometric curve flows [14] which allows for a stable numerical scheme, as well as for ....
D. Terzopoulos and R. Szeliski. Tracking with kalman snakes. In A. Blake and A. Yuille, editors, Active Vision, pages 3--20. MIT Press, Cambridge, MA, 1992.
Geometric Snakes for Edge Detection and Segmentation of.. - Yezzi, Jr., Kumar, al. (1995) (Correct)
....then we draw our conclusions in Section 7. 2 Background on Snakes In this section, we briefly review the energy based optimization approach to deformable contours as discussed in [19, 44, 10, 6] For complete details, we refer the interested reader to the collection of papers in [6] especially [43]. Let C(p) x(p) y(p) be a closed contour in R where 0 p 1. Note that the superscript T denotes transpose. We now define an energy functional on the set of such contours ( snakes ) E(C) Following standard practice, we take E(C) to be of the form E(C) E int (C) P(C) where E ....
....oe I(x; y)k; for a suitably chosen constant c, in which case the snake will be attracted to intensity edges. Here G oe denotes a Gaussian smoothing filter of standard deviation oe. One also typically considers dynamic time varying models in which C(p) becomes a function of time as well; see [43]. In this case, one defines a kinetic energy and the corresponding Lagrangian (the difference between the kinetic energy and the energy E defined above) Applying the principle of least action, one derives the corresponding Lagrange equation which one tries to solve numerically employing various ....
D. Terzopoulos and R. Szelski, "Tracking with Kalman snakes," in Active Vision edited by A. Blake and A. Zisserman, MIT Press, Cambridge, Mass., 1992.
Tracking Nonparameterized Object Contours in Video - Nguyen, Worring, van den.. (2002) (Correct)
....[2] the contour is approximated by B splines. The methods first fit a B spline curve to intensity edges and then use a Kalman filter or a Monte Carlo filter to track the B spline coefficients. In [3] Fourier coefficients are used as parameters of the contour. In several other tracking algorithms [4], 5] the contour detection is performed by minimizing some energy function, using extensions from the snake model of Kass et al. 6] In the Kalman snakes, the Euler Lagrange equation is the basis for the construction of the predicted next instance of the contour. The implementation of the ....
D. Terzopoulos and R. Szeliski, "Tracking with Kalman snakes," in Active Vision, A. Blake and A. Yuille, Eds. Cambridge, MA: MIT Press, 1992, pp. 3--20.
Real-Time Tracking of Complex Structures - With On-Line Camera (Correct)
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D. Terzopoulos and R. Szeliski. Tracking with Kalman snakes. In A. Blake, editor, Active Vision, chapter 1, pages 3--20. MIT Press, 1992.
Improving Performance of Distribution - Tracking Through Background (Correct)
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D. Terzopoulos and R. Szeliski, "Tracking with Kalman Snakes," Active Vision, A. Blake and A. Yuille, eds., pp. 3-20, Cambridge, Mass.: MIT Press, 1992.
Active Contours for Tracking Distributions - Daniel Freedman Computer (Correct)
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D. Terzopoulos and R. Szeliski. Tracking with kalman snakes. In A. Blake and A. Yuille, editors, Active Vision, pages 3--20. MIT Press, Cambridge, MA, 1992.
Comparative Analysis of Kernel Methods for - Statistical Shape Learning (Correct)
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Terzopoulos, D., Szeliski, R.: Tracking with Kalman Snakes. In: Active Vision. MIT Press (1992) 3--20
Tracking Non-Rigid Objects Using Functional Distance Metric - Laskov, Kambhamettu (Correct)
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Demetri Terzopoulos and Richard Szeliski. Tracking with Kalman snakes. In BlakeandYuille [3], pages 3--20.
Geodesic Active Regions and Level Set Methods for Motion.. - Paragios, Deriche (2005) (1 citation) (Correct)
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D. Terzopoulos, R. Szeliski, Tracking with Kalman snakes, in: A. Blake, A. Yuille (Eds.), Active Vision, MIT Press, Cambridge, MA, 1992, pp. 3--20.
Spatiotemporal Analysis Of Deformable Contours - Akgul (2000) (1 citation) (Correct)
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D. Terzopoulos and R. Szeliski. Tracking with kalman snakes. In Active Vision, pages 3--20. MIT Press, 1992.
Tracking Non-Rigid Objects Using Functional Distance Metric - Laskov, Kambhamettu (Correct)
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Demetri Terzopoulos and Richard Szeliski. Tracking with Kalman snakes. In Blake and Yuille [3], pages 3--20.
Tracking Non-Rigid Objects Using Functional Distance Metric - Laskov, Kambhamettu (Correct)
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Demetri Terzopoulos and Richard Szeliski. Tracking with Kalman snakes. In BlakeandYuille [3], pages 3--20.
Extensions of Differential-Geometric Algorithms for Estimation of .. - Laskov (2001) (Correct)
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Demetri Terzopoulos and Richard Szeliski. Tracking with Kalman snakes. In Blake and Yuille [19], pages 3--20. 175
Active Contours for Tracking Distributions - Freedman, Zhang (2004) (Correct)
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D. Terzopoulos and R. Szeliski, "Tracking with kalman snakes," in Active Vision, A. Blake and A. Yuille, Eds. Cambridge, MA: MIT Press, 1992, pp. 3--20.
Variable Kernel Density Estimation of Color Invariant Images - Gevers, Aldershoff (Correct)
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D. Terzopoulos and R. Szeliski, Tracking with Kalman Snakes, in Active Vision, Blake and Yuille (eds), pp. 3-20, MIT Press, 1992.
Merging Parametric Active Contours within.. - Ray, Acton.. (2003) (Correct)
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D. Terzopoulos and R. Szeliski, Tracking With Kalman Snakes, A. Blake and A. Yuille, Eds. Cambridge, MA: Active Vision, MIT Press, 1992, pp. 3--20.
Autonomous Sports Training from Visual Cues - Andrew Smith And (Correct)
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R. Szeliski and D. Terzopoulos. Tracking with kalman snakes. Active Vision, pages 3--20, 1992.
Robust Computer Vision: Theory and Applications - Sebe, Lew (Correct)
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D. Terzopoulos and R. Szeliski. Tracking with Kalman snakes. Active Vision, A. Blake and A. Yuille, eds., pages 2--20, 1992.
A Model for Dynamic Shape and Its Applications - Che-Bin Liu And (2004) (1 citation) (Correct)
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D. Terzopoulos and R. Szeliski. Tracking with kalman snakes. In A. Blake and A. Yuille, editors, Active Vision, pages 3--20. MIT Press, Cambridge, MA, 1992.
Deformable Spatio-Temporal Shape - Models Extending Asm (2001) (Correct)
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Terzopoulos D., Szeliski R., Tracking with Kalman snakes. Active Vision, A. Blake and A. Yuille (eds.), MIT Press, Cambridge 1992, MA, Ch.1, pp.3-20.
Tracking Objects Using Density Matching and Shape Priors - Zhang, Freedman (2003) (Correct)
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D. Terzopoulos and R. Szeliski, "Tracking with kalman snakes," Active Vision, pp. 3--20, 1992.
A Predictive Contour Inertia Snake Model For - General Video Tracking (Correct)
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D. Terzopoulos and R. Hallinan, "Tracking with Kalman snakes", Active Vision, The MIT Press, 1992, pp.4-20.
Extensions of Differential-Geometric Algorithms for Estimation of .. - Laskov (2001) (Correct)
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Demetri Terzopoulos and Richard Szeliski. Tracking with Kalman snakes. In Blake and Yuille [19], pages 3--20. 175
Detecting lameness using `Re-sampling Condensation' and.. - Roger (Correct)
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D. Terzopoulos, R. Szeliski, Tracking with Kalman snakes, Active Vision (1992) 3 -- 20.
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