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10,028
Mesh Optimization
, 1993
"... We present a method for solving the following problem: Given a set of data points scattered in three dimensions and an initial triangular mesh wH, produce a mesh w, of the same topological type as wH, that fits the data well and has a small number of vertices. Our approach is to minimize an energy f ..."
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Cited by 392 (8 self)
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We present a method for solving the following problem: Given a set of data points scattered in three dimensions and an initial triangular mesh wH, produce a mesh w, of the same topological type as wH, that fits the data well and has a small number of vertices. Our approach is to minimize an energy
Active Appearance Models Revisited
 International Journal of Computer Vision
, 2003
"... Active Appearance Models (AAMs) and the closely related concepts of Morphable Models and Active Blobs are generative models of a certain visual phenomenon. Although linear in both shape and appearance, overall, AAMs are nonlinear parametric models in terms of the pixel intensities. Fitting an AAM to ..."
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Cited by 462 (39 self)
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to an image consists of minimizing the error between the input image and the closest model instance; i.e. solving a nonlinear optimization problem. We propose an efficient fitting algorithm for AAMs based on the inverse compositional image alignment algorithm. We show how the appearance variation can be "
Multiobjective Evolutionary Algorithms: Analyzing the StateoftheArt
, 2000
"... Solving optimization problems with multiple (often conflicting) objectives is, generally, a very difficult goal. Evolutionary algorithms (EAs) were initially extended and applied during the mideighties in an attempt to stochastically solve problems of this generic class. During the past decade, ..."
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Cited by 440 (7 self)
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Solving optimization problems with multiple (often conflicting) objectives is, generally, a very difficult goal. Evolutionary algorithms (EAs) were initially extended and applied during the mideighties in an attempt to stochastically solve problems of this generic class. During the past decade
The GENITOR Algorithm and Selection Pressure: Why RankBased Allocation of Reproductive Trials is Best
 Proceedings of the Third International Conference on Genetic Algorithms
, 1989
"... This paper reports work done over the past three years using rankbased allocation of reproductive trials. New evidence and arguments are presented which suggest that allocating reproductive trials according to rank is superior to fitness proportionate reproduction. Ranking can not only be used to s ..."
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Cited by 423 (14 self)
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This paper reports work done over the past three years using rankbased allocation of reproductive trials. New evidence and arguments are presented which suggest that allocating reproductive trials according to rank is superior to fitness proportionate reproduction. Ranking can not only be used
Constrained optimal fitting of threedimensional vector patterns
 IEEE Transactions on Robotics and Automation
, 1998
"... Abstract â€” This paper addresses the problem of finding whether a given set of threedimensional (3D) vectors (the object) can be brought to match a second set of vectors (the template) by means of an affine motion, minimizing a measure of the mismatch error and satisfying an assigned set of geometr ..."
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Cited by 3 (0 self)
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based on an efficient convex optimization algorithm is proposed. An example of application of the proposed methodology to a manufacturing tolerancing problem is also provided. Index Termsâ€”Absolute orientation, automated tolerancing, computer vision, convex optimization, least squares, visual servo
A general approximation technique for constrained forest problems
 SIAM J. COMPUT.
, 1995
"... We present a general approximation technique for a large class of graph problems. Our technique mostly applies to problems of covering, at minimum cost, the vertices of a graph with trees, cycles, or paths satisfying certain requirements. In particular, many basic combinatorial optimization proble ..."
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Cited by 414 (21 self)
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problems fit in this framework, including the shortest path, minimumcost spanning tree, minimumweight perfect matching, traveling salesman, and Steiner tree problems. Our technique produces approximation algorithms that run in O(n log n) time and come within a factor of 2 of optimal for most
Flexible smoothing with Bsplines and penalties
 STATISTICAL SCIENCE
, 1996
"... Bsplines are attractive for nonparametric modelling, but choosing the optimal number and positions of knots is a complex task. Equidistant knots can be used, but their small and discrete number allows only limited control over smoothness and fit. We propose to use a relatively large number of knots ..."
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Cited by 405 (7 self)
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Bsplines are attractive for nonparametric modelling, but choosing the optimal number and positions of knots is a complex task. Equidistant knots can be used, but their small and discrete number allows only limited control over smoothness and fit. We propose to use a relatively large number
Evolving Virtual Creatures
 in SIGGRAPH 94 Conference Proceedings, ser. Annual Conference Series
, 1994
"... This paper describes a novel system for creating virtual creatures that move and behave in simulated threedimensional physical worlds. The morphologies of creatures and the neural systems for controlling their muscle forces are both generated automatically using genetic algorithms. Different fitnes ..."
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Cited by 386 (1 self)
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fitness evaluation functions are used to direct simulated evolutions towards specific behaviors such as swimming, walking, jumping, and following. A genetic language is presented that uses nodes and connections as its primitive elements to represent directed graphs, which are used to describe both
Probing the Pareto frontier for basis pursuit solutions
, 2008
"... The basis pursuit problem seeks a minimum onenorm solution of an underdetermined leastsquares problem. Basis pursuit denoise (BPDN) fits the leastsquares problem only approximately, and a single parameter determines a curve that traces the optimal tradeoff between the leastsquares fit and the ..."
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Cited by 365 (5 self)
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The basis pursuit problem seeks a minimum onenorm solution of an underdetermined leastsquares problem. Basis pursuit denoise (BPDN) fits the leastsquares problem only approximately, and a single parameter determines a curve that traces the optimal tradeoff between the leastsquares fit
Results 11  20
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