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Lowdistortion
"... lowvoltage operational transconductance value can be controlled by varying the bias voltage l.transconductance amplifier ..."
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lowvoltage operational transconductance value can be controlled by varying the bias voltage l.transconductance amplifier
Shape matching and object recognition using low distortion correspondence
 In CVPR
, 2005
"... We approach recognition in the framework of deformable shape matching, relying on a new algorithm for finding correspondences between feature points. This algorithm sets up correspondence as an integer quadratic programming problem, where the cost function has terms based on similarity of correspond ..."
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Cited by 413 (15 self)
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of corresponding geometric blur point descriptors as well as the geometric distortion between pairs of corresponding feature points. The algorithm handles outliers, and thus enables matching of exemplars to query images in the presence of occlusion and clutter. Given the correspondences, we estimate an aligning
Globally Smooth Parameterizations with Low Distortion
, 2003
"... Good parameterizations are of central importance in many digital geometry processing tasks. Typically the behavior of such processing algorithms is related to the smoothness of the parameterization and how much distortion it contains, i.e., how rapidly the derivatives of the parameterization change. ..."
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Cited by 100 (2 self)
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parameterization with low distortion. We optimize the patch layout subject to criteria such as shape quality and parametric distortion, which are used to steer a mesh simplification approach for base complex construction. Global smoothness is achieved through simultaneous relaxation over all patches, with suitable
Bounded geometries, fractals, and lowdistortion embeddings
"... The doubling constant of a metric space (X; d) is thesmallest value * such that every ball in X can be covered by * balls of half the radius. The doubling dimension of X isthen defined as dim(X) = log2 *. A metric (or sequence ofmetrics) is called doubling precisely when its doubling dimension is ..."
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Cited by 198 (40 self)
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is bounded. This is a robust class of metric spaceswhich contains many families of metrics that occur in applied settings.We give tight bounds for embedding doubling metrics into (lowdimensional) normed spaces. We consider bothgeneral doubling metrics, as well as more restricted families such as those
Low Distortion Spanners
"... A spanner of an undirected unweighted graph is a subgraph that approximates the distance metric of the original graph with some specified accuracy. Specifically, we say H ⊆ G is an fspanner of G if any two vertices u, v at distance d in G are at distance at most f(d) in H. There is clearly some tr ..."
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Cited by 25 (3 self)
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tradeoff between the sparsity of H and the distortion function f, though the nature of this tradeoff is still poorly understood. In this paper we present a simple, modular framework for constructing sparse spanners that is based on interchangable components called connection schemes. By assembling
LowDistortion Embeddings of Trees
 Journal of Graph Algorithms and Applications
, 2003
"... We prove that every tree T = (V,E) on n vertices with edges of unit length can be embedded in the plane with distortion O( n); that is, we construct a mapping f : V > R² such that #(u, v) f(v) O( n) #(u, v) for every u, v V ,where#(u, v) denotes the length of the path from u to v in T ..."
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Cited by 10 (1 self)
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We prove that every tree T = (V,E) on n vertices with edges of unit length can be embedded in the plane with distortion O( n); that is, we construct a mapping f : V > R² such that #(u, v) f(v) O( n) #(u, v) for every u, v V ,where#(u, v) denotes the length of the path from u to v
Low distortion maps . . .
, 2004
"... We initiate the study of the minimum distortion problem: given as input two npoint metric spaces, find a bijection between them with minimum distortion. This is an abstraction of certain geometric problems in shape and image matching, and is also a natural variation and extension of the fundamental ..."
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We initiate the study of the minimum distortion problem: given as input two npoint metric spaces, find a bijection between them with minimum distortion. This is an abstraction of certain geometric problems in shape and image matching, and is also a natural variation and extension
OF LOW DISTORTION BIPOLAR AMPLIFIERS
"... Heuristic methodologies for the analysis and design of low ..."
Low distortion embeddings for edit distance
 In Proceedings of the Symposium on Theory of Computing
, 2005
"... We show that {0, 1} d endowed with edit distance embeds into ℓ1 with distortion 2 O( √ log d log log d). We further show efficient implementations of the embedding that yield solutions to various computational problems involving edit distance. These include sketching, communication complexity, neare ..."
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Cited by 26 (1 self)
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We show that {0, 1} d endowed with edit distance embeds into ℓ1 with distortion 2 O( √ log d log log d). We further show efficient implementations of the embedding that yield solutions to various computational problems involving edit distance. These include sketching, communication complexity
Low distortion Euclidean embeddings of trees
, 1998
"... We consider the problem of embedding a certain finite metric space to the Euclidean space, trying to keep the biLipschitz constant as small as possible. We introduce the notation c2 (X, d) for the least distortion with which the metric space (X, d) may be embedded in a Euclidean space. It is known ..."
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Cited by 7 (0 self)
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We consider the problem of embedding a certain finite metric space to the Euclidean space, trying to keep the biLipschitz constant as small as possible. We introduce the notation c2 (X, d) for the least distortion with which the metric space (X, d) may be embedded in a Euclidean space. It is known
Results 1  10
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