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Stochastic Completion Field with Probabilistic Transition
, 2003
"... The report is to present a new simple method of using the probabilistic transition to evaluate the stochastic completion field. It is found that by quantizing the imaging plane according to the actual lineup of the image pixels, the stochastic completion field with random walks can be well character ..."
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The report is to present a new simple method of using the probabilistic transition to evaluate the stochastic completion field. It is found that by quantizing the imaging plane according to the actual lineup of the image pixels, the stochastic completion field with random walks can be well
Analytic Solution of Stochastic Completion Fields
 Biological Cybernetics
, 1995
"... We use generalized particle trajectories to derive an analytic expression characterizing the probability distribution of boundarycompletion shape. This is essential to the understanding of the perceptual phenomenon of illusory (subjective) contours. The particles' dynamics include Poissondist ..."
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Cited by 19 (5 self)
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distributed ensembles of driving forces as well as particle decay. The resulting field, representing completed surface boundaries, is characterized by the fraction of particles at x with velocity x. The distributions are projectively covariant in the sense that fields calculated in any lowerdimensional projection
Local Parallel Computation of Stochastic Completion Fields
 Neural Computation
, 1997
"... We describe a local parallel method for computing the stochastic completion field introduced in an earlier paper[Williams96]. The stochastic completion field represents the likelihood that a completion joining two contour fragments passes through any given position and orientation in the image plane ..."
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Cited by 46 (5 self)
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We describe a local parallel method for computing the stochastic completion field introduced in an earlier paper[Williams96]. The stochastic completion field represents the likelihood that a completion joining two contour fragments passes through any given position and orientation in the image
REMARKS AND ERRATA Maximally complete fields
, 2006
"... A, ” namely the condition that every polynomial of the form a0x pn + a1x pn−1 + · · · + an−1x p + anx + an+1 with each ai in the residue field k have a root in k, was shown by Whaples to be equivalent to the condition that k have no extensions of degree divisible by p. See the “Afterthought ” to “ ..."
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A, ” namely the condition that every polynomial of the form a0x pn + a1x pn−1 + · · · + an−1x p + anx + an+1 with each ai in the residue field k have a root in k, was shown by Whaples to be equivalent to the condition that k have no extensions of degree divisible by p. See the “Afterthought
REMARKS AND ERRATA Maximally complete fields
"... A, ” namely the condition that every polynomial of the form a0x pn + a1x pn−1 + · · · + an−1x p + anx + an+1 with each ai in the residue field k have a root in k, was shown by Whaples to be equivalent to the condition that k have no extensions of degree divisible by p. See the “Afterthought ” to “ ..."
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A, ” namely the condition that every polynomial of the form a0x pn + a1x pn−1 + · · · + an−1x p + anx + an+1 with each ai in the residue field k have a root in k, was shown by Whaples to be equivalent to the condition that k have no extensions of degree divisible by p. See the “Afterthought
REMARKS AND ERRATA Maximally complete fields
"... namely the condition that every polynomial of the form a0x pn + a1x pn−1 + · · ·+ an−1xp + anx + an+1 with each ai in the residue field k have a root in k, was shown by Whaples to be equivalent to the condition that k have no extensions of degree divisible by p. See the “Afterthought ” to “Maximal ..."
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namely the condition that every polynomial of the form a0x pn + a1x pn−1 + · · ·+ an−1xp + anx + an+1 with each ai in the residue field k have a root in k, was shown by Whaples to be equivalent to the condition that k have no extensions of degree divisible by p. See the “Afterthought ” to “Maximal
REMARKS AND ERRATA Maximally complete fields
"... A, ” namely the condition that every polynomial of the form a0x pn + a1x pn−1 + · · ·+ an−1xp + anx + an+1 with each ai in the residue field k have a root in k, was shown by Whaples to be equivalent to the condition that k have no extensions of degree divisible by p. See the “Afterthought ” to “Max ..."
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A, ” namely the condition that every polynomial of the form a0x pn + a1x pn−1 + · · ·+ an−1xp + anx + an+1 with each ai in the residue field k have a root in k, was shown by Whaples to be equivalent to the condition that k have no extensions of degree divisible by p. See the “Afterthought
Practical animation of liquids
 Graphical Models and Image Processing
, 1996
"... We present a comprehensive methodology for realistically animating liquid phenomena. Our approach unifies existing computer graphics techniques for simulating fluids and extends them by incorporating more complex behavior. It is based on the NavierStokes equations which couple momentum and mass con ..."
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Cited by 438 (26 self)
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conservation to completely describe fluid motion. Our starting point is an environment containing an arbitrary distribution of fluid, and submerged or semisubmerged obstacles. Velocity and pressure are defined everywhere within this environment, and updated using a set of finite difference expressions
Probabilistic Anatomical Connectivity Using Completion Fields
"... Abstract. Diffusion magnetic resonance imaging has led to active research in the analysis of anatomical connectivity in the brain. Many approaches have been proposed to model the diffusion signal and to obtain estimates of fibre tracts. Despite these advances, the question of defining probabilistic ..."
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Cited by 1 (1 self)
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connectivity indices which utilize the relevant information in the diffusion MRI signal to indicate connectivity strength, remains largely open. To address this problem we introduce a novel numerical implementation of a stochastic completion field algorithm, which models the diffusion of water molecules in a
From Stochastic Completion Fields to Tensor Voting
"... Abstract. Several image processing algorithms imitate the lateral interaction of neurons in the visual striate cortex V1 to account for the correlations along contours and lines. Here we focus on two methodologies: tensor voting by Guy and Medioni, and stochastic completion fields by Mumford, Will ..."
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Abstract. Several image processing algorithms imitate the lateral interaction of neurons in the visual striate cortex V1 to account for the correlations along contours and lines. Here we focus on two methodologies: tensor voting by Guy and Medioni, and stochastic completion fields by Mumford
Results 11  20
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2,258,653